We selected eight users for usability testing. We wanted to find users who drove EVs since the app was geared towards EV drivers. However, we ran into an issue where no one in the group knew any drivers who drove a fully EV and we were unable to find anyone who drove a fully EV either. We were able to find two drivers who drove Hybrid electric Vehicles (HEV). The other participants all drove gas vehicles. While it would’ve been ideal to have our participants all be EV drivers, the drivers would still be able to partake in the usability testing as long as they drove a vehicle. No specific demographic was targeted although we did make sure to note the ages of the participants. Also we wanted participants that had varying amounts of experience when it comes to mobile apps.
Our first goal was to understand EV driver preferences when it comes to apps and charging stations. Afterwards, we wanted to find innovative solutions to the problems that EV drivers face. We then wanted to make an app that felt would benefit EV drivers.
Virtual Assistant Settings
Virtual Assistant Interface
Prototype
After coming up with the features that would make up the core of the EV charging app, we ended up making a prototype. The prototype incorporated each of these features seamlessly. The prototype lets users find charging stations through searching for them or by picking their locations on a map. Users can also put filters in order to help them find the charging stations, put filters to help them find charging stations, see recommendations from the app, set up a virtual assistant and use that assistant for finding charging stations.
Finding and Navigating to a Charging Station by Searching:
After coming up with the features that would make up the core of the EV charging app, we ended up making a prototype. The prototype incorporated each of these features seamlessly. The prototype lets users find charging stations through searching for them or by picking their locations on a map. Users can also put filters in order to help them find the charging stations, put filters to help them find charging stations, see recommendations from the app, set up a virtual assistant and use that assistant for finding charging stations.
Finding a Charging Station by Using the Map:
The user finds a charging station to go to. However, instead of using the search bar, the user selects an icon on the map screen that will belong to the corresponding charging station. User’s can use a legend to differentiate between the different types of charging stations.
Recommendations:
When viewing a charging station, users get to see an overview of the station, when clicking on the review button, users get to see reviews of the station and see what others think about it, and when users click on photos, they can take photos of the station.
Virtual Assistant:
User’s can use the virtual Assistant by using the microphone which is located at the bottom of the screen and will change colors when used. The Virtual Assistant can be used for various tasks in the app such as navigation, changing settings, planning trips, etc.
Setting up a Virtual Assistant:
Setting up the virtual assistant up can be done by first clicking on the account icon at the bottom right hand corner of the screen. Then user’s can click on the Virtual Assistant Settings options and make the Virtual Assistant active. If they click on the Virtual Assistant Notifications options, they can then adjust various aspects of the Virtual Assistance Notifications.
Filters:
A filter button is located on the right hand side of the search bar. Clicking on it will pull up a filters menu. Using this menu, users can apply filters based on a variety of categories such as availability, plugs, distance and network.
After users completed their interviews, we had them complete a survey in order to get their overall thoughts about the app. Users were asked various close ended and open ended questions. The close ended questions would typically be multiple choice and users would have three to five options when answering a question. Open-ended questions tended to be free responses. that would help us identify different usability problems with the app and get recommendations for what to fix about it.
Satisfaction with the app was high, this may be contributed to design of the application itself and the features offered. In Fig. 17 Respondents indicated a high chance of recommending the application to others based on their experience. A high contributing factor of satisfaction is the accuracy and the provision of the most current status of charging station availability.
The responses of the survey provide valuable insight into the preferences, and behaviors of drivers using driver assistance applications. These findings can allow future developers of applications similar to this to be able to develop the most user friendly and ergonomic application that would be used by EV vehicle owners.
We selected eight users for usability testing. We wanted to find users who drove EVs since the app was geared towards EV drivers. However, we ran into an issue where no one in the group knew any drivers who drove a fully EV and we were unable to find anyone who drove a fully EV either. We were able to find two drivers who drove Hybrid electric Vehicles (HEV). The other participants all drove gas vehicles.
While it would’ve been ideal to have our participants all be EV drivers, the drivers would still be able to partake in the usability testing as long as they drove a vehicle. No specific demographic was targeted although we did make sure to note the ages of the participants. Also we wanted participants that had varying amounts of experience when it comes to mobile apps.
Our task analysis focused on pinpointing the potential factors that care the most about when it comes to picking a charging station. I made a sequential diagram that focused on showing an EV driver’s actions so that we could understand the EV driver’s decision making process. The sequence of events has users checking the state of their EV and then deciding to go on a trip. Then the user receives a notification from their EV app informing them that their EV is low on charge so they start trying to figure out a place to charge. Using the app, they look at recommended charging stations and decide to go to one of the charging stations. They drive to the station they want to go to and charge their vehicle.
Through our task analysis, we deduced that notifications that used real time data and recommendations were important factors for EV drivers when it comes to deciding where to charge their EV. I ended up making a hierarchical analysis diagram that would help the group get a more in depth examination of a driver’s needs for each task.
We brainstormed different features that could go into the EV charging app. Then we put those features and ideas into a mind map. Then secondary features would be created beside off of the main ideas.
One of our team members created sketches in order to get a basic idea of the app's design. The 3 sketches shown here showcase different ideas for how the default map page should be presented.The sketches included features for locations, filters, recommendations, virtual assistant and the navigation bar.
Intro
Electric Vehicle (EV) drivers deal with a number of issues when it comes to going and getting their cars charged. This is largely due to limitations in current EV charging structure. They often have to deal with long and extensive wait times. EV drivers often have to take many factors into account when traveling like the availability of cars per location, the quality of service, the distribution of stations and more.
Project Goals
Our first goal was to understand EV driver preferences when it comes to apps and charging stations. Afterwards, we wanted to find innovative solutions to the problems that EV drivers face. We then wanted to make an app that felt would benefit EV drivers.
Research
Literature Review
Task Analysis
Mind Map
Sketches
Task Flow
Usability Testing
Survey
Me and two other members in the group created literature reviews to understand the preferences of EV drivers and the factors that influence their charging station choices. Some of the focus areas for us when deciding on the research papers to look at were the accessibility and convenience charging locations, compatibility issues due to the mismatch between a vehicle's requirements and a station's capabilities, and how much low maintenance and charging costs influenced drivers to adopt EV’s.
In terms of our findings, we discovered that the majority of EV charging happens at home, which suggests the need for improved EV infrastructure to accommodate that. We also learned about how public places are important charging places and yet are under supported. We got further insights into how availability, cost, compatibility affect user choices and satisfaction. Something else that stuck out to us was the need for policies that enhance infrastructure to support growing EV usage.
While these apps did each have different user interfaces that showcased their unique user characteristics. They all shared a lot of similarities such as focusing on helping EV drivers find charging stations, providing them with information such as a country's charging speed and cost, providing users with recommendations, etc.
We carried out a remote moderated usability study through Zoom so that we could gather insights on the behavior of EV drivers and their preferences when using the mobile app to navigate to a charging station. The study touched on ideas such as navigation, content insights, overall satisfaction, areas for improvement, and unmet needs. Participants were given access to a Figma link. They completed four tasks with one task having two sub-tasks. Before the participants completed the main tasks, we asked them five preliminary questions.
Qualitative Analysis
Preliminary Questionnaire
1.a Finding and Navigating to a Charging Station:
Participants were tasked with navigating through a flow to locate EV charging stations. They found it pretty easy, generally speaking, to identify the nearest charging station and to start their trip using the app. However, one participant was initially confused and didn’t realize that the search bar could be used to find a specific location.
1.b Finding and Navigating to a Charging Station Using the Map:
Some participants were able to recognize the icons and their intended meanings. Many associated the bolt icon with fast charging and interpreted the pause icon as indicating unavailability or full capacity. The red color was universally understood as a signal that a station was unavailable. However, participants suggested improvements, such as adding legends or keys to clarify icon meanings. Additionally, they found the legend icon less intuitive and had difficulty locating the legends button on the screen.
2. Filtering and Searching for Stations:
Participants were tasked with searching for a charging station based on specific criteria, including compatibility with their vehicle’s plug (J-1772), proximity to restaurants, availability, and network affiliation. Most users quickly identified the filter icon and successfully completed the task, despite a few prototype constraints. Overall, participants were satisfied with the available filter options.
3. Finding Recommendations:
Participants were asked to select a charging station based on positive reviews. Overall, they were able to locate reviews from other EV drivers with ease and were satisfied with this feature.
4.a Setting Up Virtual Assistant:
Participants found configuring the virtual assistant's notifications to be straightforward, suggesting that the settings menu is well-organized and the options are clear. Users rated this task as easy, indicating that the virtual assistant settings are intuitive and user-friendly. However, one participant preferred the option to activate the virtual assistant from the first screen, allowing for quick activation while on the go.
4.b Interacting with Virtual Assistant to Find a Charging Station:
Participants found the interaction with the virtual assistant very easy, indicating that the voice-activated features are responsive and intuitive.
Recommendations:
A key recommendation was the addition of an alert system that notifies drivers when they are approaching their last opportunity to charge before exceeding their vehicle’s range. This feature would support critical decision-making and significantly enhance the app’s usability.
Overall:
Overall, participants were able to complete tasks with ease, aside from a few limitations due to prototype constraints. Additionally, some participants encountered issues understanding the meaning of various location icons on the map and had difficulty identifying the legends button on the screen.
Post Survey Findings
The open-ended questions on the post survey allowed us to collect some qualitative data from the participants. The participants' observations about the tasks included that sometimes the icons were confusing, and it would benefit to show what the icons mean, like with a legend. Others mentioned that the app was well organized and concise, and it was easy to navigate through the different sections and features. Another participant commented that sometimes it was straightforward what to do, and sometimes it needed to be clarified. Finally, one participant said it allowed easy navigation, preventing the driver from becoming distracted.
When we asked participants what the most essential features of a charging app were, they said that navigation and EV charging, a map to find the charging stations, search and map, and the ability to notify them when their car must be charged so that they do not become stranded needing a tow, to let them know where the nearest charging station is, were the most important features. One participant indicated that using voice commands on a phone while driving is very dangerous. Additional features and improvements were mentioned by participants, such as incorporating text with the icons, the ability to calculate the most efficient way to travel long distances with the least downtime charging, or with other search constraints, such as the ability to set up a trip with Lodging and restaurants that have charging stations. One participant mentioned that the colors could have been more brightly and friendly.
Finally, a participant mentioned that the virtual assistant should be a feature on an existing map/navigation application. Others said that it was a pretty good app overall, and they liked the idea of having an app with this purpose.
Quantitative Analysis
Our application focused on finding a charging station with ease with different tasks that were asked of the user. The satisfaction levels shown in Fig. 3 with the driving app were generally positive, with 50% of respondents expressing extreme happiness and the remaining 50% reporting mild or moderate satisfaction. In Fig. 4, satisfaction with the user interface was also high, with a 67% majority somewhat satisfied and the remaining participants extremely satisfied.
The survey results in Fig.5 show that the most valuable features of the EV app were the inclusion of the map view of the charging stations, real-time availability of the charging status, and reviews from the other drivers. These results illustrate the value of providing practical and informative features.
Usability Testing Task Findings:
Recommendations: Delete the ratings and star icons entirely from the search page. This eliminates any confusion the user may encounter when seeing distance and review ratings right next to each other. If the user needs to see the reviews for a station. Once they click on the page for a location, they will be able to see the review ratings and be able to read full reviews of a station.