The following case study focuses on the challenges faced by urban commuters. Currently, finding parking spaces in increasingly congested cities is becoming a greater challenge. According to statistics, nearly 30 percent of traffic congestion is caused by people searching for parking spots. In some cities, this can take an average of 10 to 20 minutes, and in particularly congested areas, it can take even longer. On average, people waste 17 hours a year driving around looking for parking. The goal of this case study is to design a multifunctional mobile application that assists drivers in finding free and paid parking spaces and streamlines the parking process in urban settings.
1.LACK OF PARKING SPOTS:
Many drivers spend a significant amount of time searching for a vacant spot, which leads to frustration,
delays, and wasted time. Finding a parking spot near their destination can become a real challenge,
especially during peak hours or in packed areas.
2.NO UPDATES ABOUT PARKING SPACES:
Another frustrating problem is the lack of real-time information on parking space availability.
Often, drivers are unsure if a particular parking lot is already full or if a space has become
available after their arrival. This uncertainty leads to inefficiency and the need to take risks,
which can result in wasted efforts and frustration.
3.INSUFFICIENT INFORMATION ON PARKING DETAILS:
Drivers often encounter the issue of not having information on parking fees, the operating
hours of paid parking zones, and any restrictions, such as maximum parking duration. The absence of
this information makes parking planning difficult and exposes drivers to penalties or charges for
non-compliance with regulations.
4.OTHER PARKING-RELATED
INCONVENIENCES:
Furthermore, there are many other inconveniences associated with parking in a congested city.
These include difficulties with parking space dimensions and heights, the lack of amenities such as
electric vehicle charging or access to public restrooms, and the absence of electronic payment
options, requiring drivers to have cash on hand.
To gain further insights, I conducted five brief interviews with drivers based in Vienna. These individuals use their cars on a daily basis and park them in similar areas every day. Additionally, I have prepared a concise survey consisting of 10 questions. The interviews were conducted using a combination of phone calls and in-person meetings. What's important is that none of the users are using parking apps.
The quantitative research findings are summarized as follows:
The qualitive research findings:
Daily street parking search is a common occurrence. Users often find themselves late for work, meetings, or simply feeling frustrated due to the time spent searching for a parking spot. Another common situation is being forced to park a considerable distance from their destination, which is also perceived as a time loss. Users sometimes struggle to remember where they parked the next day. Frequently used words include "stress," "confusion," and "time waste."
So, yes - nothing new under the sun. However, even these insights are capable to provide valuable clues, such as the need to establish a clear information architecture with an emphasis on displaying data like the distance from home or offering solutions to find the parking space in the proximity to the destination.
Based on the survey data, I have identified some of the most common characteristics of the main users.I have created a persona representing the user's key characteristics, goals, and frustrations. Additionally, I have included in the persona what should and should not be taken into account in the project. None of the biography, educational history, medication history, shoe sizes or such nonsense. Sorry, wrong story.
To discover an unexplored niche within the parking application market, I developed a Market Positioning Chart utilizing four key parameters. I then positioned the top 10 most widely used applications on this chart. The outcome revealed that the sector with the least competition is the facilitation of street and free parking discovery. This segment has been highlighted as the "blue ocean" on the diagram, signifying its untapped potential in the market. Consequently, I have chosen to allocate greater attention and resources to this promising, untapped domain.
In contrast to most applications of this kind, my project, besides offering the ability to find and book paid parking spaces, emphasizes a greater focus on locating street parking. For the project to be successful, it must provide value to drivers, facilitating their intended actions, and it must be implemented considering the context of driving in a congested city.
To determine the necessary information users need to see and identify which functionalities should be implemented, I have created more than 30 user stories organized into three categories: users searching for curb parking, users seeking paid parking, and users wanting to return to their car. In this particular case, user stories were created to list the type of information and functionality that should be included in the application. The "independence" category indicates to what extent a given functionality can exist independently, without being linked to other functions.
The insights gained from the user stories have guided me in identifying the functionalities that need to be implemented throughout the entire application. To provide a clearer understanding, I have categorized them into six distinct categories.
Before embarking on the creation of wireframes and user flows, the final step involved developing the information architecture for the entire application. The key element is the bottom navigation, which serves as the starting point for essential functionalities such as searching for parking, payments manager, and an car assistant. Various display modes for parking types and views can be activated using the FAB.
The subsequent step involved creating rough wireframes of the app and defining user flows for the key functionalities. The given wireframes depict the basic tasks: booking a parking place and seeking a free space out of charge.
All prototype screens were made in Figma. The screens are 360 × 800 wide.
There are a number of more or less obvious conditions that create the context for using such applications. I tried to take these conditions into account when making design decisions.
In the application project, I've implemented two custom solutions. One of them has a broad application, allowing for an intuitive integration of parking spot search with GPS, relieving the driver from the need to constantly refer to street maps. The other solution is more narrowly applicable and serves as an experimental concept that can be used in specific scenarios. Both functionalities are unique and are not used in the parking applications I have benchmarked.
This is a solution aimed at enhancing the user experience within the application. It involves routing the user through streets where there is the highest likelihood of finding a parking spot at that particular time. The feature automatically generates the route and displays information about it, and it is accessible with just two taps. The aim of this functionality is also to alleviate cognitive load on the driver. A driver using the application must demonstrate divided attention – they need to search for parking, drive the vehicle, and glance at the application. This feature reduces the need and frequency of checking the map, especially since I would also suggest implementing voice navigation.
1.The application allows for multiple ways of displaying parking spots, whcih could be found under the FAB. One of the options is the graphical highlighting of streets where it is currently easier or more difficult to find a parking spot (this is technologically feasible; I have conducted a benchmark of the application, and similar mapping are used by apps like Waze or SpotAngels). The user is notified about the areas where they currently have the best chances of quickly finding a parking spot. An additional advantage of this feature is that the user can see which streets they have already checked, eliminating the need for unnecessary wandering. Furthermore, they have access to a timer that helps them assess whether it's worth repeating that route.
2.The user can navigate to their destination by either selecting a pin on the map or simply using the in-app map. Alternatively, they can make use of the "Set a Route" option. Upon activating this feature, the application calculates a route consisting of interconnected streets marked by the app as potential parking locations. The user is guided in a manner similar to a traditional GPS, following the designated streets. There is an option for "Loop the route," which guides the user along the established route until they find a parking spot. Additionally, there's a "Next route" option, where the application suggests an alternative route in the vicinity.
The application allows for multiple ways of displaying parking spots, whcih could be found under the FAB. The functionality allows tracking places that have recently been marked by other users as vacated by them. When a driver marks in the application that they are vacating a spot, it becomes visible to other users. Those users can then use their points to reserve the spot for themselves. I would consider implementing automation for marking vacated parking spots using GPS and user movement speed measurements.
1.This functionality allows users to view recently vacated parking spots in a specific location. The marker indicates the location and the time when the spot became available, aiming to assist the driver in making a decision on whether it's worth heading to that spot. To utilize this feature, drivers must also notify other users when they are vacating a parking spot, earning points that they can later use to check the availability of recently vacated spots.
2.The driver can allocate a portion of their points to reserve a spot, which becomes visible only to them, and they are navigated to it. This is an innovative and somewhat risky solution; however, I believe it may have applications in specific conditions, as outlined in the SWOT analysis below.
I am aware that this solution has limited applicability and may not work in certain conditions. Therefore, I have also prepared a SWOT analysis to outline the positive and negative aspects of the functionality.
The application utilizes a hub-like information architecture model, where the user has access to all other key functionalities from a central location, which is the dashboard/home. On the home screen, the "Search Nearby" feature serves as the call-to-action (CTA). Other key sections are accessible through the navigation menu
The bottom navigation comprises four items: user profile, parking search, payments, and assistant. The default screen upon opening the application is the map view, which allows for quick and easy parking spot discovery.
The maps enable finding free street parking spaces, checking the likelihood of finding parking on a particular street, and identifying areas of the city covered by paid parking zones.
I've categorized the features in the map view into two groups. The primary features are placed under the FAB (Floating Action Button) and allow for switching between display modes for parking on the map (paid parking, availability of street parking, vacant spots). The secondary features are concealed within the bottom sheet and are directly related to location-based functionalities, such as result filtering, marking a location on the map, and reading saved locations.
The FAB (Floating Action Button) allows switching between display modes for parking spots, such as showing areas with easy parking, recently vacated parking spots, and between types of parking, whether they are free or paid.
The "search" option allows users to both view results on the map and access a list of search results.
The set of tools includes features such as displaying the remaining time on a parking ticket, providing the distance from the car's current location, allowing users to extend their parking time, indicating the car's location, and providing an estimated time remaining to reach a parking spot. The "car assistant" functionality enables users to locate their parked car (using a directional arrow pointing to the parking spot as well as on the map), track and extend parking payments.
The user can filter search results using filters divided into basic and advanced categories.
