Have you ever been frustrated trying to find parking in a busy urban area? To address this problem, we designed Parko, an augmented reality (AR) in-car voice-controlled assistant, to help urban drivers find parking efficiently.
(The project is based on the assumption that the data of parking lots information and the real-time parking situation is available. See more relating reflection in the Reflection section )
April 2018 - June 2018 (8 weeks)
Cecelia Zhao, Sarah Chu
Task analysis, functional storyboard,
user flowchart, video filming & editing.
Indesign, Photoshop, Illustrator,
After Effect, Premiere Pro
How might we design a product to help drivers find suitable parking in the busy urban area efficiently?
We learned that parking could be broken down into 3 key steps:
Driving around to find an empty spot
Evaluating the spot
Parking the car
The pain point of find parking lays in its first two steps. When the driver finally finds an empty spot after a long search, he still may not be able to park due to limitations such as price, time limit, and distance to destination. Then he will have to find a new spot again.
OBSERVATION & PHOTO ANALYSIS
With our design opportunity in mind, we made more observation and conducted a photo analysis. During the observation, we asked our participant to find parking in a shopping area
with multiple parking lots.
Drivers in the busy urban areas need assistance to find suitable parking efficiently because they don't have access to key decision-making information in advance.
sketches selected for final design direction
ideation process: organizing the sketches
With our point of view statement in mind, we brainstormed and organized 30+ ideas. We then evaluated these ideas based on three criteria: viability, desirability, and feasibility.
After narrowing down to one concept, we fleshed out the interaction model of our product and created a functional storyboard.
We identified two main user personas：
The planner: this type of users prefer to planning out where to park before they set off for a destination.
The reactor: this type of users prefer to getting to the destination first and then figuring out where they want to park.
We created a user flowchart that communicates the experience flow of the two type of user when they use Parko to find parking.
Show a parking map that allows users to browse and select parking lots near the destination before setting off.
Display parking lot info to help drivers choose a suitable parking lot efficiently.
Navigates users to the selected parking lot.
Indicate whether users can park in specific spaces within the parking lot.
Reflection and Action
The data needed for this product include:
Information of parking lots such as prices, time and location
Real-time information of available spots in the lots.
Is it feasible to collect all these data needed? If so, who should be collecting the date and who are the stakeholders?
Consider turning the project into a practical product with different phases:
Revise the product so it only requires the parking lots information and leaves out the real-time data. Even consider integrating the product into an existing product such as Google Map.
Explore the possibilities of the collection of real-time data and consider who is the appropriate stakeholder.
We did well on considering the balance between AI decision making and user decision making. But we should also take into consideration that rich information given to the users might compromise driving safety.
Re-examine all related design decisions (user personas, preference setting options, information displays) Conduct more research and testing.