Designing the User Experience of
as Mobility on Demand Services (Part 1.)
Autonomous vehicles (AVs) can make a significant meaningful difference to the world, enabling a new level of mobility, behaviors and safety for all. AVs will hit the roads in only just a few years. Maybe one day when you wake up, all these new vehicles will be everywhere around you. Solving the technical challenges is one thing. But on the human side, the bigger challenge is how to increase mass adoption of AVs into mainstream commuters and drivers.
There is more than just getting from 'home' to 'work'.
What people really need is mobility, they want to get from 'home' to 'work' safely and comfortably. For sure, the technology could simply facilitate and support this. But for us as designers, the question is what are people’s mobility needs and wants and how can autonomous vehicles support them?
Let's Talk about the Process.
Learning from other resources
Before directly delving into primary research, we conducted a literature review to get a grasp of issues surrounding the design of automobility. The dearth of literature on designing interactions for fully autonomous vehicles means we have to reach to resources from ancillary disciplines, including sociological and anthropological studies of automobility, and also technical documents and guidelines for interface design for vehicular systems.
User research to find problems and gather insights
We used research methods such as directed storytelling, word-cloud association, semantic inquiry, think-aloud and participant observations to collect enough data. Then we consolidated all this data and synthesized them into findings and insights. Based on our insights, we got our design focus to guide us.
Directed Storytelling Exercise
We conducted a directed storytelling exercise with 7 participants, gathering customers’ stories to understand what people valued in mobility on demand services, and their various needs. We were particularly interested in see their perceptions towards people around automobility and what past experiences with cars have shaped these perceptions.
Qualitative Control Study
We designed this control study in 3 phases (pre-ride, ride-along and post ride) to understand social and personal imaginaries, the conceptions and mental models that people had around driving and ride-sharing, their attitudes and expectations on technology and to find out how they as passengers might think, feel and react to being driven in an AV.
The sample of seven participants that we drew for this study belonged to an existing market segment for mobility on demand vehicles - young working professionals within an age demographic of 25 - 40 not working in the IT or technology sectors.
After gathering our data, we put our notes on individual post-it notes and created data buckets in the form of an affinity diagram. This affinity diagram allowed us to naturally group related ideas. After grouping ideas, we created higher level data buckets that encompassed the overall messages and themes of the various groupings. Our completed affinity diagram helped reveal our main findings and insights.
In the process of making affinity diagrams
By analyzing and synthesizing the data we gathered, we were able to get to the heart of the matter and see what our research was telling us. These realizations will help us formulate what specific areas and problems our solution needs to target.
We answered questions related to ride-sharing services, human control in AVs and questions directly to AV itself. And, If you are interested in details, please contact me, I would be more than happy to share more with you!
Here comes out our design focus
1. How might we help passengers
better understand of how the AV works?
2. How might we increase visibility of
AV’s internal state and its decision making process?
3. What is the best way to calibrate appropriate expectations
of the AV’s abilities in passengers?
Iteratively polish and craft design
We created three different personas, with each having very different requirements and values, focusing on what they each valued in terms of mobility-on-demand services, what their driving and riding habits and practices were establishing context of use, and key behavioral characteristics like sociability towards other passengers or driver, personal driving style, motor awareness and optimism regarding novel technologies.
We identified nine crucial scenarios that we would need to design for an autonomous mobility-on-demand system, and sketched a number of scenarios focusing on the details of the interactions.
We started by sketching out and exploring different directions and ideas on paper for both the external parts of the car system and the internal interface. We started by identifying the various parts of the car that could house either digital, screen based or tangible, physical interfaces. While this sprint does not focus on tangible interactions and interfaces, the two particular interfaces we are currently focusing on are a System notifications through an LED screen above the car windscreen and a Redesigning the Ottoview interface, with three distinct views into it.
On-road prototype : wizard of Oz
For more information, please reach me out via firstname.lastname@example.org:)
I would be more than happy to share more.
BTW, we also conducted another user study (include user interview, role-playing exercises, love&breakup letter exercises, plea-card exercises) focusing on working professional commuter passengers, trying out to understand their motivations and different transit selection strategies, also what they valued in their daily commute.