Adding Augmented Reality to Dublin Bus app

Dublin Bus app.
More than 500,000 downloads.
App Store rating 1.9; Google Play store rating 3.0.
Is it possible that Dublin Bus is failing not only giving their customers accurate information, but also failing to give them the access to it?


🚌 Introduction

In the past few years, mobile technologies have rapidly become the focus of all users’ attention, resulting in people being online most of the time. People use their smartphones everywhere and for almost any purpose – from checking Facebook while sitting in a bar or paying for groceries with a single swipe, to video chatting while out for a walk.

The use of mobile technology is prevalent in every part of daily life. In light of how social media and technologies are developing, and due to the fact that the virtual and real-world are being brought closer together, it is easy to predict that the next step could be reality embellished with virtual elements.

Taking the word ‘augment’ as a starting point, which means to make greater or improve, augmented reality (AR) could be characterised as an expanded or enhanced real world. This is usually achieved using computer vision technology through the use of mobile devices (smartphones, glasses etc.) to overlay digital elements on our view of the real world, thus creating an illusionary perspective of the same place. The components of the virtual world are usually text labels, 3D models, animations and graphics, projected on the real world and seen by the user through a camera.

By allowing overlapping additional information on top of the real world to give a new level of information display, AR has the potential to become an important part of everyone’s day-to-day life and to change the way people interact with the world. For example, when a user wants to get information from their smartphone, they have to move their focus between the physical space and the phone, which can cause difficulties when engaging with the task. Using AR, the information space can be merged with the physical space, showing the right information in the right context.

Augmented reality has gone from being a fantasy to a reality in less than a century. Even though there are many AR apps on the market today, the technology will only see increased uptake when it actually starts to improve performance, productivity or experiences. It needs to solve real problems or improve and enhance current experiences for users.

There is evidence that this is slowly happening, as AR has already been integrated into numerous apps where products can be presented to the user in greater fidelity or in context. For example, IKEA Place lets users place furniture in their home through the lens of a smartphone camera, and Mercedes has an AR assistant that lets drivers scan any part of their car and have its functionality explained in a user-friendly way.

The latest topical reference to the subject is Google’s AR-powered virtual zoo, which has 3D animals that a user can view in their living room. The virtual zoo does not require any specific app and can be used by searching for an animal, for example an alligator, and then scrolling to the results and tapping ‘view in 3D’.

This seemingly simple interaction invokes a realistic 3D animated alligator right into the space where the user is. It went viral after launch, providing an amusing and wondrous distraction during the COVID-19 social distancing crisis. Millions of photos of people with these virtual wild animals at home have been shared with awe around the world. This recent example shows just how ready users are to accept AR if it is easy to use.

📱 Mobile Augmented Reality

Augmented Reality has been on the market for more than 60 years but has only become popular in the last decade when it became mobile. Mobile augmented reality (MAR) is augmented reality that a user can take with them wherever they go, meaning that the device with the AR application has to be completely mobile. This device can be a smartphone, tablet, glasses or any other hardware with a camera and a screen that can give the user a view and insights into an object.

The procedure is as follows. A user captures a scene through their smartphone, tablet, or glasses, and the device processes, identifies and displays the digital elements inside the real-world view, in real time. The first MAR apps were mainly focused on gaming but more recently they have covered many domains including navigation, real estate, education, architecture and interior design.

Depending on the type of mobile device where AR is implemented, there are three archetypes:

  1. The first archetype is based on handheld augmented reality (HAR) mobile devices. Smartphones, tablets and phablets are considered to be the most popular HAR devices. They contain all the hardware needed for an AR system to work: the camera to capture a video of the real world, a display to present the enhanced world, and a processor to generate digital elements and merge them with the video.
  2. The second archetype is based on see-through devices, usually AR glasses, through which users can see both the virtual world and the real world with their own eyes. Augmented reality glasses could be the best solution for MAR but because of their weak processors and low power, most apps for glasses are still quite basic.
    One of the main differences between HAR and see-through devices is that smartphones and tablets require at least one of the user’s hands, while AR glasses do not. Because of the size and the weight of HAR devices, they can raise ergonomic issues relating to pose, grip and controller allocation. As well as these ergonomic issues, they can also raise perceptual issues, which relate to understanding the information presented in context.
  3. The third archetype is known as monitor-based AR, where the processor and monitor are not contained in a single device. This type is normally used when the camera has to be autonomous or when large displays are required (e.g. in augmented endoscopy).

🚎 Public transport in Dublin

Public transport in Dublin consists of a bus network, a heavy rail line (DART) and two light rail lines (the Luas). The leading bus operator, Dublin Bus, manages a fleet of 1,074 buses, which operate across 136 routes and approximately 5,000 stops. 

Figures announced by the National Transport Authority (NTA, 2019) reveal that 31% of routes did not complete their targets in 2018, and only 17% of Dublin Bus routes could be trusted to reach their targets. According to the NTA report, Dublin Bus received the most complaints from its customers about issues related to routes and service.

In 2014, Dublin Bus released a mobile app for Android and iOS. With more than 500,000 downloads, this app rates 1.9 (out of 5) on the Apple Store and 3.0 on the Google Play Store. Based on 4,682 customer reviews (4,419 on the Google Play Store and 263 on the Apple Store), it is possible to see how Dublin Bus is failing not only to give their customers accurate information but is also failing to give them access to it. 

In 2010, Dublin Bus started rolling out a real-time passenger information (RTPI) system, which displays the amount of time before the bus arrives at the next stop. Because of the high cost of implementation and maintenance, the system is not implemented at all bus stops. Some stops still only display the stop number as a referral code, meaning users have to key the code into their mobile app to get real-time information there.

The Dublin Bus mobile app has more than 500,000 users, and it relies heavily on the RTPI system. In order for a user to find out the bus’s arrival time at a specific location, they have to perform a search by bus stop number.

If the user does not know the bus stop number, finding the bus arrival time becomes a more difficult and complicated task than it should be. The user is required to check the bus number and its route on the map, which rarely works, then find the bus stop location and its number, and hopefully get the arrival time.

If it happens that users need information other than the arrival time, for example, the available buses at a bus stop, routes, or the last stop, then they have to complete separate interactive tasks to do so. This may take a couple minutes longer to find out, during which time they may have missed a bus at a nearby stop. Given that more than 325,00 people use the Dublin Bus service every day, bus stops should be a key touchpoint to improve overall engagement and customer experience.

📱 Augmented Reality in Public transport

Bad user experiences at bus stops is an ongoing issue in all major cities but it can be resolved by providing accurate data about bus arrival times and passengers’ end-to-end journeys. Technologies like AR could be the right tool to make transport networks simple enough to be used by everyone and personalised to an individual’s needs. Augmented reality apps could potentially result in transportation systems being more efficient and safer for all. For instance, by pointing their phone towards the bus stop, users could get real-time information and view the bus route on a map without wasting too much time.

Maps can be confusing sometimes. If someone is struggling with their sense of direction, they could easily turn right instead of left before they even realise that they have made a mistake. Google Maps resolves this issue by introducing AR functionality into its Android and iOS apps. After the user enters the desired destination, they are prompted to either start in a normal way or with a live view.

Google Maps Live
Google Maps Live

Only the beta version is available in Ireland, but the example above shows how the application works. By mixing the real world with digital elements placed exactly above crucial locations, it gives the user accurate walking instructions that lead them to their destination.


👣 Design Process

The design process is divided into four phases – discover, define, develop and deliver – as described in the Double Diamond model. The notoriously beneficial feature of this model is the emphasis on divergent and convergent thinking. During the discover and develop stages, many ideas are created and are easily narrowed down in define and deliver stage.

double diamond
Double Diamond framework

The focus in the Discover phase is on learning more about the variables that might influence the main challenge and the ultimate solution. During this stage, the goal is to spot and investigate the actual problem.

In the second phase, Define, the focus is on reviewing and narrowing down the insights from the previous stage to define the main challenge to be resolved.

This is followed by the Develop stage, where the actual design process commences, creating the solution to the problem defined in the previous two phases.

The final stage, Deliver, includes testing and releasing the product to the public. Even though this might seem like the end of the work for a designer, it can often mean that the work has only just started. 


🔑 User Problems and Product Opportunities

The objective of the Discovery stage is to recognise and contextualise the actual problem or opportunity. Activities considered in this stage include market research and testing with users, with a primary focus on users’ needs, wants, and behaviour.

When looking to find the problems that the users have with the product, there shouldn’t be place for assumptions as they can often be wrong. The only right way to find out the users’ real pain points is getting them by analysing supporting data, which can be found using:

  • User interviews
  • Surveys
  • User feedback and reviews

🎤 User Interviews

Interviews can be described as ‘conversations with purpose’, where the approach depends on the objective of the interview. For the purpose of this testing, unstructured interviews took place, which means the questions were exploratory and the session was more like a conversation about the participant’s experience with Dublin Bus and their general attitude to AR. For the purpose of this research, only existing users were interviewed (seven users in total) because the focus was on their pain points and daily habits related to Dublin Bus.

🖌 Conducting the interviews

Four interviews were conducted in person, while remaining three were conducted via an online phone call. Four interviews were recorded, while in the remaining three only notes were taken.

Before starting, all participants were asked to sign a consent form agreeing to be the part of the study. After gathering the feedback from all interviews, similar data was bundled together and organised into themes using affinity diagrams. This method provides an effective way of grouping information collected during research, and helps to understand the relations between groups of information and to synthesise the findings.

🧩 Findings

After grouping similar feedback together and creating themes, some key issues were highlighted. These included the difficulty checking the bus arrival time when the bus stop number is unknown and ‘hacking’ the flow by replacing the Dublin Bus app with Google Maps, often just to find out which buses go to which destination.

The majority of participants also stated that they check the bus arrival time before they leave their house/apartment, but when they do not know the bus stop number, the time to get the information increases significantly.

📋 Questionnaires

Online questionnaires are normally used to collect data about users’ demographics, their habits/behaviours and their opinions, using open and/or closed questions. Questionnaires can be delivered to a wider audience in an online form, which means more qualitative and quantitative data can be gathered.

For the purpose of this research, the questionnaire was created using Google Forms and contained two sections. In the first section, participants were asked about their previous experiences with Dublin Bus. In the second section, they were asked about their attitude towards AR. No demographic data was captured. The majority of the questions were multiple-choice questions containing predefined answers but with an additional option to input free text.

🧩 Findings

In order to ensure it was clear and without ambiguity, the questionnaire was piloted and evaluated on three participants before distribution. After the questionnaire was refined, it was sent to participants via a range of social network channels including Slack, WhatsApp and Facebook.

The questionnaire was completed by 73 individuals, comprising friends, students and colleagues. Data collected was stored in Google Forms, where individual responses and summary information were tracked. The analysis of the data followed, using quantitative statistics. The result was organised sets of data with the response representation of each question. 

More than half of respondents used Dublin Bus at least once a week, if not more. A total of 87% of the respondents checked the bus arrival time before taking the bus. The majority (73%) of respondents used the Dublin Bus app to check the bus arrival time, while 20% used Google Maps or the TFI RTI app. When asked, ‘Do you always know the bus stop number?’, 80% of participants answered ‘No’, which means the time to find the information on bus arrival takes even longer than normal. 

Apart from the information on the bus arrival times, 47.3% of the respondents highlighted that they would like to see the bus route and the bus stops displayed on a map, while 43.6% wanted to see the exact cost of the journey. A total of 63.6% of participants wanted to know if the bus was empty or full, because when the bus is full, the bus drivers do not stop at the bus stop, so they have to wait for another bus. When asked if they had any issues with finding the bus stop, 42.3% of respondents had a positive answer and 37.5% did not know which side of the road the bus stop was on. 

In relation to AR, only 30.2% of respondents said they had used an AR app; 52.4% said they had never used an AR app and 17.5% stated that they did not know what AR is. When asked how useful they think the AR app they had used was, most of participants answered between 5 and 7 (useful) on the 1–7 Likert scale. When asked whether AR could be of benefit when used in public transport, 54.5% participants answered positively, while 27.3% thought the opposite.

To summarise, the majority of respondents used Dublin Bus more than once a week, and they all had similar issues when trying to find information on bus arrival times. In the absence of knowing where the bus stop is, respondents had their own way of ‘hacking’ the system and getting the information in another way. From the data gathered from both online questionnaires and interviews, three possible scenarios of use were mapped, as shown below.

Possible scenarios diagram
Possible scenarios diagram
  1. When the bus stop number is known, the user opens the Dublin Bus app, inputs the bus stop number, and gets the arrival time. The task is complete.
  2. When the bus stop number is unknown, but the bus number is known (80% of users), the user opens the Dublin Bus app, searches the route using the bus number, checks the map (which is often not working properly), finds the bus stop number, and then gets the arrival time. The task is complete.
  3. When the bus stop number and the bus number are unknown, and only the destination is known, the user opens Google Maps, inputs the destination, checks the bus lines that can take them to that destination, opens the Dublin Bus app, searches the given bus route, opens the map in the app to find the exact bus stop, and then gets the arrival time. The task is complete.

⚔️ Competitor Analysis

In this section, direct and indirect competitors will be analysed in order to have a better understanding of where the opportunities and threats are. By focusing on customers first and filling gaps where they exist, the outcome should be a better product that provides a more enjoyable service. For the purpose of this research, both a competitor analysis and an analysis of strengths, weaknesses, opportunities and threats (SWOT) have been conducted. 

In the competitor analysis, the Dublin Bus app was analysed along with four direct competitors (Transport for Ireland Real Time Information [TFI RTI], Moovit, Next Bus Dublin and Bus Times London) and two indirect competitors (Google Maps and World Around Me [WAM]).

The features are highlighted in the product screenshots and were defined as follows: 

  • AR functionality
  • Display of trip duration
  • Viewable route map
  • Option to save favourite stops
  • Alert to take the bus
  • Search by bus stop
  • Accurate real-time information on bus arrival time
  • Search by location
  • Option to view nearby bus stops

From this list of features, only three were found in the Dublin Bus app: the option to save a favourite stop, bus stop search and the display of nearby stops, which was buggy. The key feature that Dublin Bus customers want is accurate real-time information on bus arrival times, but two other direct competitors, TFI RTI and Next Bus Dublin, already display this information in better way. 

Competitor Analysis
Competitor Analysis

💪 SWOT Analysis

In the following section, a SWOT analysis of the strengths, weaknesses, opportunities and threats was carried out. The strengths and weaknesses (internal) of the Dublin Bus app were identified, followed by identification of the opportunities and threats.

Even though this type of analysis is normally used to identify the key factors of a business’s value chain, it can also be used to analyse the effectiveness of a site or app. The main reason why a SWOT analysis is performed is to identify the factors that are important for a site or app to be successful and to map those that could be harmful.

There is a possible danger that competitors with more advanced apps will replace the Dublin Bus app altogether. For example, Google Maps is often used instead, even though the arrival time it displays is retrieved from the Dublin Bus schedules, which are often not accurate.

SWOT analysis
SWOT analysis

Problem statement

How can we speed up the current process of finding a bus stop and checking the bus arrival time?


👟 Stepping into users’ shoes

After all the data was gathered during the first stage, the definition stage followed. In this stage, the focus is on reviewing and narrowing down the insights from the previous stage to define the main challenge to be resolved. This was carried out using the visual representation of a customer’s journey, which helped to identify the problems with the current service.

👤 Creating a user persona

Personas consider the ways of thinking, behaviours, goals, and attitudes of a wider group of users and funnel them into a specific user type. After the data gathered from interviews and surveys was analysed, two types of persona were created: primary and secondary. 

The primary persona, Conor, has a range of goals that align to the main focus of the AR prototype design developed for this research study. Conor moved to Dublin from Galway two weeks ago. He started a job at Salesforce in Central Park and his first working week has just commenced. Conor does not own a car so he has to take Dublin Bus every day in order to get to work. He has to calculate the time it will take to reach the bus stop from his home or work, which will determine how early he has to leave. He has to check the bus stop numbers of all the bus stops where he will take the bus so that he can check the bus arrival time.

Primary persona, Conor
Primary persona, Conor

The secondary persona has a few specific needs that are not the primary persona’s priority. The secondary persona, Grace, lives in Dublin now but is originally from Leeds, England. She is working at Workday, and this year she enrolled for a master’s degree at University College Dublin. Her home is in Tallaght, her office is in Smithfield and her college is in Belfield. Grace does not own a car; instead, she takes the Luas to get to work every day. Twice a week, she has to take the Dublin Bus to go to college in Belfield. On those days, she is very tired so she wants to use her time in the best possible way and not waste it waiting at the bus stop.

Secondary persona, Grace
Secondary persona, Grace

Mapping both primary and secondary personas at this stage was extremely important as it helped to place the focus on users and understand their concerns. This resulted in the creation of an app with a realistic user journey, aimed at satisfying user needs and expectations.

🎭 Empathy Map

An empathy map, like a persona, is also used as a guiding light throughout the design process. It gives a detailed portrayal of the given user types by answering four simple questions: what the user thinks, says, does, and feels.

Overall, empathy maps are great tools that help designers understand users better, gain empathy, and get familiar with their behavioural patterns.

Empathy Map
Empathy Map

Empathy map was used to enhance empathy towards the user, categorise and make sense of qualitative research data and discover the possible gaps in the research itself.
It also served us as a quick way to show users’ behaviours, thoughts, and attitudes to other members of the team and stakeholders. It’s crucial to keep the empathy map updated as more research is done.

🎢 Customer Journey Map

A customer’s journey is usually defined as a map of the phases and emotions that a customer experiences while using a certain product or software. Two customer journeys were created for this project. One of them describes the situation ‘as-is’, while the other shows the desired ‘to-be’ situation.

Mapping the as-is journey allows the current customer experience to be understood in a better way and highlights the areas where customers’ expectations are not met. In this case, Conor has to get the information on bus arrival time using a third-party app (Google Maps) and then switch back to the Dublin Bus app, which takes more time than he expected and makes his experience cumbersome. 

As-Is Journey Map
As-Is Journey Map

In the to-be journey, the process of finding a bus stop is improved using AR, which makes Conor’s experience of using the app seamless. The requirement for this project is to improve the current experience of users when they want to find the bus arrival time but only know the destination.

To-Be Journey Map
To-Be Journey Map


🖍 Let’s design

In this stage of the Double Diamond framework, the actual design process commences, creating the solution to the problem defined in the previous two phases. It was important to understand the context in which users would be interacting with the new prototype Dublin Bus app, which is why user scenarios were developed before prototyping.

⏳ Prototyping in Figma

Figma is a cloud-based design tool. It works on any operating system and runs via web browser. Design projects can be shared and distributed using an invitation or by sharing a link. This made the design process, prototyping and testing smooth and easy. An entire worksheet, all screens and iterations are available in Appendix F.

For the purpose of this project, iOS Human Interface Design was chosen as the design library. This decision was not only because the device that the prototype was tested on was an Apple iPhone, but also because it offers a rich collection of quick-to-use views and controls, and options to customise some elements. This library was also considered to be the preferred option because of the clarity it provides and the simplicity of the elements it contains. The components used on the screens were taken directly from the iOS kit, which meant that changes between the iterations were easy and the style used throughout the app was consistent.

The first screen contains a map, with all the nearest bus stops marked using icons. If the user wants to know which buses could take them to a certain area, they can use the input field at the top of the screen to key in their destination. This results in a filtered search, showing only bus stops with buses driving to the desired destination. 

New landing screen with a map
New landing screen with a map

⏳ Prototyping in Torch

The second part of the new prototype required software that supports AR. Two AR creation apps were reviewed: Adobe Aero and Torch. Even though Adobe Aero has better visual performance, meaning there is less ‘glitching’ involved, Torch was selected because it has a wider range of functionality.

In Torch, it is possible to change between ‘scenes’ using different interactions, while Adobe Aero did not have that functionality at the time. This functionality added considerable value to the prototype as more scenarios could be included, such as different bus stops with different routes and instructions. All digital objects used in the app were primarily designed in Figma and saved to the device (Apple iPhone). Then, they were uploaded to the Torch library and from there they were used in different scenes.

To navigate through each scene, interactions need to be added. As can be seen in diagram below, the entire user flow created using Torch consists of seven scenes. When landing on the results scene, the user sees three main dialogues showing the bus stops and buses that can take them to their destination (in this case, Central Park). By tapping on any of these dialogues, the user sees a new dialogue that gives them more detail on the bus stop and the bus. After tapping the start button on any dialogue, the first instructions on how to get to that bus stop are shown. By tapping on it, the user is brought back on the main scene, where they can explore other bus stops.

Torch uses a markerless augmentation approach, so each digital object has its own coordinates. The user has to set the anchor point first in order to view all elements. 

Diagram showing the users' flow when using the AR app
Diagram showing the users' flow when using the AR app

As AR is an emerging field, there are few best practice examples as yet. However, Google’s AR Design team (2020) has provided foundation research in a set of basic guidelines for designing AR experiences.

The first recommendation is to define the size of the physical space that users need for the AR app, as the experience should fit into their physical surroundings. In this case, the ‘world’ size was chosen as the dialogues would be displayed outdoors, mostly by users scanning the world around them while looking for a bus stop.

Defining the physical space
Defining the physical space

Because users would be looking through their phone camera and probably ignoring the outside world, they could bump into other people or objects and miss noticing other dangers around them. To prevent this, all digital objects were created with 70% transparency, which helps users to see through them and avoid hazards.

Adding transparency to digital objects
Adding transparency to digital objects

None of the tasks involve the user moving backwards, which is considered one of the most dangerous actions when using AR apps. In the second iteration, additional safety warnings for users to look around and check their surroundings were added to prevent any further risk. 

As suggested by the Google AR Design Guidelines (2020), all AR objects should engage with their environment and face the same direction, towards the user. Using the Torch app, this was achieved by using the ‘face camera’ functionality, which automatically turns objects towards the user.

Even if the user turns away, the object becomes visible from all sides, enabling the user to engage with the object in the best possible way. The reset process also makes it quick and easy to create a loop after three scenes have been viewed. In this way, users can easily go back into the experience. No pop-ups were used for any interaction, as users need to focus on the scene itself instead of being interrupted. 

Each element has its own x, y and z position values, which are relative to an anchor coordinate that was previously set up. This was a sensitive part of prototyping, as elements in the sequence had to be in the same position after a user had interacted with them. 

Digital objects and their sequence
Digital objects and their sequence


📱 Test. Iterate. Test

The final stage, deliver, includes testing and releasing the product to the public. Even though this might seem like the end of the work for a designer, it can often mean that the work has only just started. Once the final product is live, users provide feedback that is typically acted on and reflected in the next iterations of the design. 

🕵️‍♀️ Testing with users

For this research, forty users, both male and female, were recruited in order to gather accurate results. Once each participant had read and signed the consent, they were asked to carry out a task that involved finding a bus stop and checking the bus arrival time using the app of their choice and the prototype Dublin Bus AR app.

🔍 Findings

The findings from the pilot usability testing were as follows.

  • 60% of users were not aware that they could not get the RTPI on Google Maps.
  • All users first checked Google Maps to find out which buses could take them to their destination and then checked the Dublin Bus app to get the RTPI.
  • Users did not understand whether the icons were buses or bus stops.
  • Users needed additional confirmation that the buses displayed were the buses that could take them to Central Park.
  • Users wanted to see the arrival time at the destination displayed in the final AR dialogue.

🪜 Iterating towards the final product

After gathering feedback from the first version, the prototype was modified and prepared for the evaluation phase. The changes were as follows.

  • Replacing the Google Maps screenshot with a Mapsicle map showing Dublin city centre
  • Introducing tabs for stops and buses to counteract the confusion experienced previously when users did not understand whether the icons were buses or bus stops
  • The icons were replaced with a skeuomorphic bus stop sign. 
  • Additional information on the bus’s destination was added to the flow as previous user feedback showed they needed reinforcement on this topic.
  • The brand title was removed when the keyboard is active, which resulted in more real estate for displaying the map.
  • The second version also contained changes to display the arrival time with the destination and add additional bus and bus stop icons in the AR view. 

🥇 The final product

And this all leads to the final product.

Check the video via this link

Dublin Bus AR app

🔦 Results and analysis

The final evaluation phase consists of a comparison of the time needed to find the real-time bus arrival information using any app of choice (in most cases participants used Google Maps in combination with the Dublin Bus app) and using the new AR Dublin Bus prototype app. The method used was within-group testing, a quantitative comparison of time on task in each scenario. The participants were asked to rate their experience by filling in the HARUS questionnaire. 


⏱ Time on Task

Time on task is the one of the best ways to measure efficiency and productivity. It refers to the time a user spends completing a certain task. Even though there are different ways to analyse the task duration, this study measured task completion time, which is the time the user took to complete the task.

The findings show that the time it took to finish the task was significantly higher when the app of choice was used, compared to the time taken when the prototype Dublin Bus AR app was used. Users needed from 80 to 200 seconds to finish the task using their app of choice. However, to finish the same task using the Dublin Bus AR app, they needed from 40 to 90 seconds, with most taking 60 to 80 seconds to complete the task.

Therefore, when finding real-time bus arrival information from Dublin city centre to Central Park, the time to complete the task was significantly higher when participants used an app of their choice compared to the time it took to finish the same task using the prototype Dublin Bus AR app. 


👍 Usability

All HAR applications have to be carefully designed and also improved based on feedback from users. For this project, the HARUS was used and the feedback was captured using Google Forms.

The mean HARUS score for the prototype Dublin Bus AR app is 91.25. Bearing in mind that the HARUS is evaluated in the same way as the SUS, a score of 70 or above is required for an AR app to be considered usable, which means that the Dublin Bus AR app is usable.

From the results gathered, it appears that the time on task does not affect the HARUS score, meaning that the users who managed to finish the task in less time did not necessarily give a higher HARUS score. 


🔢 Qualitative results

Qualitative data was generated from the questionnaire given at the end of the session, where users were asked, ‘How do you feel about this technology and would you use it?’

The feedback received was mostly positive. Users noted that, if the app were available in real life, it would definitely save them time when looking for information on bus stops and bus arrival times. Some users were pleasantly surprised with seeing the information displayed using AR as they were not expecting it.

They thought displaying the information in this way would shorten the time it usually took them to get it. They liked the fact that they could view the bus stops around them and compare the distance as well as the bus arrival time all in one go, which made it easier when deciding which bus to get. 

🔑 Key Contributions

This research project has proven, through both qualitative and quantitative analysis, that using the correct set of data and principles and involving users in the design process can considerably improve the user experience.

By introducing AR into the Dublin Bus app, the time users need to find information on bus arrival times and bus stop location was significantly reduced. Other key items that were found in competitor apps were also added into the newly designed AR prototype, such as trip duration, arrival time and the ability to search by location on a map.

This resulted in reducing the time users would normally need to get the same information using the Dublin Bus app. It also addressed some of the key issues for Dublin Bus app users, one of them being, ‘if you don’t already know how to get where you want to go this won’t help’.

Following the AR prototyping process, the author suggests the following set of tips, which can be adopted by any company looking to introduce this emerging technology in their app.

  • Have a sense of the context and the world around users of the app. 
  • Make your user interface accessible during sunny, rainy and cloudy days, as well as at night.
  • Make things easy to find. In the case of working on a public transport app, have in mind that users might be rushing somewhere and they need to find the information as quickly as possible.
  • Categorise the information in your app. Some information is more important than others. Organise it into a hierarchy that shows you understand it.
  • Listen to your users. Something that may seem very obvious to designers will not be obvious for everyone.
  • Iterate your design after testing.

The quantitative data gathered in this study shows that AR functionality definitely reduces the time users would normally need for finding information on bus arrival times. It also proves that users are not afraid of this emerging technology; they are ready for it. 

⚖️ Conclusion

The aim of this study was to compare how users search for real-time bus arrival information using apps of their choice and the prototype Dublin Bus app with AR functionality. The user experience design goal of the research was to find a way to improve the overall experience for all users.

The pilot and evaluation phase had 40 participants in total, and both qualitative and quantitative methods were used in the design process. The final evaluation used a between-group design, quantitative comparison of time on task, the HARUS measurement tool, and captured qualitative data about whether the users were ready for this emerging technology or not.

The research showed that the time to execute the task was reduced by 51.56% when AR functionality was incorporated into a new prototype Dublin Bus app. The results collected from the HARUS survey, on a scale from 0 to 100, resulted in an average score of 91.25. This signifies an ‘A’ grade, which means that people loved the app and would recommend it to their friends.