SEO UX DESIGN RESEARCH LAB
Graphic Design and Media, B.S., University of Nevada, Las Vegas (UNLV)
Research group: Samari Pedraza, Ryan Pineda, and Marco Salinas
Research accomplishment: 
- Spring 2024 Undergraduate Research Symposium (Research Presentation)
​​​​​​Title: Autonomous Public Transportation Application for Las Vegas
Research Keywords: User Experience (UX), User Testing, Autonomous Vehicles, Public Transportation
Abstract: With the integration of AI technologies, an autonomous vehicle in Las Vegas could provide a more efficient way to improve the quality of public transportation. This study aimed to get users access to autonomous public transportation efficiently through user-centered design. Our study aimed to develop a smartphone application to provide riders with a unique travel experience customized to their specific preferences. These features included user-oriented navigation, ride-sharing options, and easy communication with customer support. To ensure the effectiveness of the application design, we conducted usability testing, collecting and measuring data on 1) task completion time and click errors, 2) user behaviors when interacting with the application, and 3) the initial user experience through survey questions. Our usability testing aimed to assess user acceptance, ease of use, and suitability. Despite 83.3% of participants lacking experience with autonomous vehicles, all were open to the concept. However, the application proved more challenging to navigate than expected, with surprising features. Task performance varied: Some tasks showed higher efficiency and user-friendliness, while others presented greater complexity. These findings underscore the need to refine the app's design and functionality for better user satisfaction and task efficiency. This study identified user-centered features that would enhance autonomous public transportation while focusing on Las Vegas tourists. Usability testing results will continue to drive the development of a new type of public transportation system integrating AI technology to provide tourists with a faster and more convenient means of navigating through Las Vegas.
Research Question and Hypothesis: How does the integration of AI technologies in the VOLT app impact the user experience and efficiency of public transportation in Las Vegas? Our hypothesis is that with the integration of AI technologies, public transportation in Las Vegas can become more efficient and accessible, improving the quality of service for all residents and visitors. By incorporating AI technology, the app will address common issues within public transportation, such as overcrowding, safety concerns, limited routes, and delays. We expect increased effectiveness in route optimization and safety features, leading to higher user satisfaction, shorter wait times, and safer travels. To test our hypothesis, we conducted user testing with a sample of Las Vegas residents. By observing their interactions with the VOLT app, we gained insights into how users navigate the interface, which features are most utilized, and where improvements can be made.
Branding: The logo consists of two designs, a primary and a secondary logo. The primary logo is a name logo that uses a San serif typeface. One version of the name logo can be seen in black and the second version can be seen in the blue and green gradient. The secondary logo is an icon of a pinpoint with a bolt across it. The lightning bolt symbolizes speed and efficiency, while the pinpoint represents a location or a destination. 
Development of Mobile App: VOLT is an application that serves as a gateway to Las Vegas’ public transportation systems. Although VOLT’s app interface and design resemble popular ride-sharing apps, it is not a traditional ride-sharing platform where users can request rides from independent drivers. Instead, VOLT is a public transportation service that provides users with easy access to the VOLT autonomous transportation vehicle in Vegas. This distinction is important as VOLT aims to enhance the public transportation experience with a familiar and user-friendly interface while offering the convenience of a city-wide transit system. To gain more insight into the important features of designing a public transportation ride-sharing application, we explored successful ride-sharing apps such as Uber and Lyft. These apps allow users to request a vehicle that takes them from one location to another. Their effectiveness lies in their simplicity, enabling users to customize their routes and easily find a nearby driver. During this exploration, we considered features that would allow users to have a quicker and higher quality ride, such as allowing the AI to cater specifically to the user in different aspects, including navigation, ambiance, and customer service.
User Flow Task: For our user journey we focused on 3 main features–getting a ride, exploring Las Vegas attractions, and destinations, and customer support. The design of the user flow was aimed to highlight each feature across the apps’ main pages while thoroughly explaining how users should interact with them. In Task A, upon opening the VOLT app, users will be prompted to either ‘Log In’, or to create an account. During account creation, users will be asked to provide a username, email address, and phone number, and to create a password. Additionally, they will be required to upload their ID, as well as complete payment details. In Task B, users are able to type in a destination or select from their saved destinations when planning their route. They are also given the option to add additional routes before choosing between the 3 available ride options. Once they have selected their preferred ride, they are presented with the route details and can proceed to the nearest VOLT station to continue with their journey. In Task C, upon completing a ride, users would be given the opportunity to leave feedback on how satisfied they were as well as given an area to leave final comments. In Task D, users can use the explore feature to discover popular destinations, attractions, and events in Las Vegas. The explore feature uses AI algorithms to recommend users' destinations based on places they’ve visited. Users can also read information and write reviews as well as save a location or add it to their route. A successful completion of this would be for users to discover places in Las Vegas enticing them to add it to their current or future routes. In Task E, users would be instructed to report a lost item. This involved the user to start at the Support feature and select the second option from Customer Support. After selecting the Report button, the user would be asked whether or not they are in the vehicle. If the user is not in the vehicle they would be given the options to either message or call a customer support representative. However, if they are within the vehicle they would show the vehicle the item through the camera and then be prompted to place the item in the lost bin.
Usability Testing: We found that 100% of participants opted to either use a personal vehicle, or carpool for their daily commute rather than use a bus. The reason why participants did not use public transportation such as a bus, is because they often experienced issues with limited accessibility, delays, and safety concerns. Meanwhile, 83.3% of our participants expressed a reluctance to use ride-sharing apps regularly due to the lack of driver availability at certain times, unreliable arrival times, and safety concerns. 83.3% of participants have never been in or used an autonomous vehicle before, while 100% of participants are willing to consider it.
Findings: In Task A, participants 2 and 3 took a long time on this task due to users trying to input information, however, in the Figma prototype you can not physically type. Therefore participants kept trying to click to input information. Participant 1, also had to re-click some buttons due to long fingernails. We noted that we needed to make some of the buttons larger. In Task B, participants 2 and 4, spent more time on this task, as the user kept clicking on the search bar to type. We also had problems with the Figma prototype glitching and delaying clicks. Some users would also click too fast or double-click. This brought to our attention a few wiring issues we needed to fix. Task C was overall completed successfully, with a few users needing to re-click one time. In Task D, participants did not spend as much time exploring (going through various categories) as much as we would've liked. However, participants found it successful in terms of finding various Las Vegas attractions. We did find a wiring issue when users tried to add destinations to their routes. Finally, in Task E, participant 1 spent more time on this task due to delays from the prototype and having to click various times. Overall we noticed that participants needed to double-click a few times, or would try to type in the prototype causing them to click multiple times.
Final Feature Additions: Upon completion of user testing, we were able to come up with additions to the application of the vehicle that would allow for more interaction with the AI of the vehicle. These few additions we decided to add were an emergency stop button as well as an option to quickly ask the AI about any safety issues or concerns. Another addition was a vehicle interaction control panel which allowed the user to be in control of their ride experience. In the first 3 screens show how the vehicle will always have a safety and monitoring section at the side of the application at all times to ensure that anyone can quickly stop the vehicle in an emergency or talk to the AI to make a decision or help in any emergency. The final screen shown at the right of the Safety and Monitoring section is for the vehicle’s control panel which would allow the user to customize different features within the vehicle during their ride.
Conclusion: Overall, participants were very willing to attempt to ride an autonomous vehicle since it would be considered a new way to travel around Las Vegas. However, our application does not reach high ease of use. Through our study, we were able to determine that the application had sections that did not properly prompt the user to do specific actions which led to much confusion. It was also determined that although 3 out of 6 users had an easier time navigating through the app, they still did not fully take the time to explore the app further. With our findings, we aim to continue finding and improving a solid application that makes users want to have an autonomous vehicle that will cater to their needs and provide an easier way to interact with the AI vehicle.​​​​​​​