Autonomous driving in everyday life

Digital Design Methodologies
M.Sc. Digital Service Design, Brunel University

How might we integrate autonomous driving seamlessly in the everyday lives of people?

Designbrief   The case studie deals with the question of how the integration of autonomous driving might take place in the near future within an urban context. The research focuses on the use of autonomous cars in the everyday life of people in consideration of its impact on urban life and places.

When it comes to autonomous driving, people can go everywhere at any time they want. This freedom causes new driving behaviours, needs and problems which first have to be identified. These new driving habits will also have an impact on our cities and urban life. The challenge for the automotive sector will not only be about answering how people will drive, but also considering the context of why, where and when users will move. 

There are no longer fix hotspots like bus or train stations and car parks. Is it therefore possible to define drop-off zones for driverless cars which ­create value for the user by creating a new digital meaning for phyiscal urban places? When using an autonomous car, the user has to tell the car what to do. The case studie deals with the interaction between user and car and how micro services could add a magical feeling to everyday travel issues.

Autonomous driving
When it comes to autonomous driving, the business model "mobility as a service" will arise. There will be on-demand fleet vehicles available with a subscription service (e.g. Pay-as-you-go). This means access to mobility for everyone on a daily use.

Urban Places
It is through human activities that urban spaces become places. In a future where autonomouse driving is established, physical and digital is connected in real-time. Urban places will become more fluid and temporary. Open and shared spaces like co-working and co-living will belong to the everyday life and create a city which is build around people.

No more fix hotspots
When it comes to autonomous driving, there aren't any more fix hotspots like train stations or car parks. The project HubCab from the MIT Senseable City Lab shows in real-time urban data streams where, how, and at what times different parts of our cities become stitched together as hubs of mobility. Freedom will be a challenge for people. They can go everywhere and at any time they want. What are those hubs? Where will they be?

New drop-off hotspots
People using autonomous cars will define new hubs and hotspots in the city. Is it possible to give physical places a new valuable digital meaning? How can we motivate people to go to certain places? Which opportunities will lie in the transition process between pick-up and drop-off and its relation? 

Objectives   Help users to master their everyday travel issues and offer them the „best“ options. Motivate users to go to certain places. Integrate physical urban places and give them a new digital meaning. Inform users about places with real-time data. Let users discover and explore new places. Integrate autonomous driving seamlessly into their every day life.

When it comes to autonomous driving, the challenge for the automotive sector will not only be answering the 'how', but also considering the 'why''where' and 'when'.

Strategic positioning of the service   The service can be implemented by every company which operates a fleet of vehicles. This could be manufacturing companys like Audi and BMW or service providers like Lyft and Uber. The following concept should be understood not as a stand-alone app or service, it should be seen as micro services which will operate in existing digital ecosystems.

Project approach    The project has the aim to discover the area of a possible integration of autonomous driving in an urban context. Information about autonomous driving and smart citys as well as user insights about their driving behaviour and use of current transportation and mobility services has been discovered. Within an iterative process the problem has been defined and afterwards a possbile solution has been designed.

The discovery

During the research I used following tools and methods: Brainstorming, Interviews, Card sorting, Social Media Analysis, Personas, Journey Map, Storyboards, Rapid + Live Prototyping, Wireframes


User Insights

I conducted user and market research to drive the planning phase. These are the key insights that defined the service:

Transportation is activity driven
The main goal of the primary segments are customers using a transportation service to go to specific places. It is through human activities that urban spaces become places.

Places remain the same
Customers mainly go to about five different places a week. The most traveled places are their work and home. Relevant information about locations are stored in their calendar, emails, adresse books or other apps like messenger.

Structured driving behavioure
Most of the customers creating routes to plan their journey. They combine different places in order to be more efficient and safe time.

Discover new places
The places where customers go, often reflect their personality. They are open to discover new places but especially related to their individual interests.

Lean-Back in-vehicle time
During the ride, customers are enjoying the environment, listen to some music, have a chat, thinking about their daily activities and what they will do at their place of destination.

Service to save
Especially the young customers are often willing to pay for transportation as less as possibl. Therefore they are deeply interested into getting the cheapest price with the best conditions.

Social media insights   For the social media analysis I choosed Uber and Lyft as a suitable research subject because there are many similarities of their service. I recognized that users often drive to recurring and favourite places. Therefore they need a place to safe these places, to enable a faster and easier access. It also shows that there is a lack of user satisfaction in using current applications in several every day life situations.

The user research ends up in five different personas and user groups.

The first skteches of the service end up in five storyboards. Each of them tell a story of how the service will be used in the users daily life.

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Customer Journey Maps

The Journey map explains the service in all relevant stages and which touchpoints are affected.

First Concept
The first concept focuses on the user experience during the ride. The moment of truth can be found in Stage 5 "Ride". The concept dealed with an implementation of a destination based enteratainment system. During the ride, the user gets information about his drop-off place.

Final concept
The final concept focuses on the awareness & inspiration phase. Through micro services the user gets automatically notified about possible rides which fits in the context. Instead of searching for something the user will get the relevant information he needs, in the right moment. In the morning he will be notified about going to work and a car will be automatically booked in advance. Through calendar information the user gets offers about fitting solutions. These little services will have a big impact on the experience and usage of the whole service and might be the most valuable asset for the user.

Understanding the context

For a best possible user experience, it is important to gain information about users and the context in which they are.

Context of the user
The user is situated in an enviroment with rich context information. To be able to offer the right information at the right moment it is important to know the context the user is in. This could be the location, daytime, weather, historical actions and experiences, mood or its surrounding community. The combination of all these factors can generate an accurate picture of the users situation which is helpful to decied not only what kind of information the user needs in the moment but also how to provide them. The information can also be used for prediction of further actions and behaviours.

Context of urban places
Places will also offer a wide range of information which could be important to provide the user a best possible service experience. Context information can be tracked by sensors and other tools. These information might be useful for prediction and making relevant offers for the user.

Transition process

During the ride, not only user behaviours and needs but also the environment will change. These changes have an immense impact on the users mood and experience …

Change of light during the day   One big influenece on the mood of the user has the daylight which shapes the environment. It changes during the day and depends on many environmental influences. The light is different while driving in the morning to work from going back home in the evening. For a seemless integration of autonomous driving in the everyday life it might be useful to consider those environmental influences.

Change of user activities and mood   During the day, user activities will change. Usually the user goes to work in the morning. In this situation it is also important to understand in which mood the user is. He might be tired and want to relax during a ride from home to work. When it comes to a ride during the day or in the evening, the activities will change as well as the mood and expectations of the user. With information of the users current location and its final drop-off, the mood transition process from one to another activity might be have a positive influence of the user experience.


The service for autonomous driving consists of three key elements: Micro Services, Smart Places with New Digital Meaning.

Use Cases   A use case for each persona was created. Each use case is related to possible situations, which are typicall for each user group. The storys have different focuses with a varied use of the service key elements. Usually it is an interplay between all key elements which create the experience.


To define how the service works on mobile devices, sketches were created to test different ideas.


The service is created for mobile devices because it is currently the most used device of the target group and offers a lot of possibilities.

Key elements   The app exists of a conversational interface which is the centerpiece. During the conversation the user has an overview about the current live status of the vehicle. If the user has booked a car it shows when the vehicle will arrive and what the destinatio will be. To communicate with the vehicle, input actions will give the user an easy access to common commands. Conversations are designed to be answered with Yes and No to allow a quick and easy conversation.

Personal fleet vehicle   Everytime the user books a ride, the next available fleet vehicle will come for pick-up. To feel that it is everytime the same vehicle the user can give it a name. The conversation is designed to feel natural and is written from the "I" perspektive. During the use, the system learns from the users behaviour and will adapt to it.

Transition process   To create a seamless integration, environmental influences are considered and integrated in the experience. The conversation will automatically adapt and react to the users situation with help of colours and light. It will pick up the environment and adapt to it to create a most personalized feeling.

The most important functions of the conversational interface are visualized with help of wireframes, to explain how it works.

For each persona a short use case is created. The screens give an insight about typicall interactions and visualize the use cases.


Backstage functions

A lot of context data of the user is required, to create a proactive instead of a reactive user experience. Data like favourites, conntected apps/services and payment methods are stored in the user profile.


Smart places   Beside the conversational interface the user gets access to a lot of additional information. There are detailed map views and detail informaion about places. The content of those pages depends on the kind of place. For example a branded place differs from a public institution or private adress.


To test and evaluate the idea of communication between car and user, rapid prototyping with a common messanger app was used in the first instance.

Low fidelity prototyp    First I used a messenger app to test the chat conversation between user and car. How will the users react to the messages and what will they reply. I tested it in a natural environment with some sample use cases. I send messages in the morning before going to work, during the day and in the evening. I ask the people for their plans they will have for the day where they have to use a train or car to get there. In one test I accompany the person and in an other I was not next to them and they were on their one.

Pixate    For bringing the screens to live and see how the app works, Pixate was used to create a clickable prototype of three different screens: 1. Usability of the input actions, 2. The general navigation between conversation, car and profile and 3. the behaviour of the conversation.

The ride experience

Totally personalised in-vehicle experience which focuses on the transition process from A to B. The experience will transform users mood to prepare him for his destination. It is a different ride going to work every morning than to a football match with your friends in the evening. Each situation needs to be a different experience. The in-vehicle system will react to the context and will seemlessly adapt to the users situation.

In-Vehicle display   The experience should feel like that the car adapts completly to the environment and situation of the user. Therfore the display should be as small as possible. The display is 360° and sits under the windows. The user should experience the real environment and notice the digital as a merge from the outside to the inside.

Wireframes   For getting a feeling how the service might work in the car, rough wireframes show key interactions in the vehicle. From the first welcome screen, to interactions during the ride and finally for leaving the vehicle.

Other Touchpoints

The case study focuses only on the key touchpoint "Mobile" to give an insight how the service might work. This touchpoint is most used during the ongoing use of the service.