Overview:
'Jump Control is a fleet management and teleoperation web application that solves last mile logistics for small electric vehicles such as e-scooters and robots. ' With the help of Jump control, we uncover the scooter -sharing problems.
The popularity of e-scooter-sharing services have changed the face of how many travel around cities. While these services have given rise to a range of benefits – from faster travel to less congestion – cities are struggling to deal with the negative effects such as poor riding behavior and an increase in accidents.
As a UX/UI designer, I collaborated with a startup engineering team developing a physical product and an intelligence platform capable of upgrading any scooter-sharing service to include a suite of ‘smart’ services.
The Problem:
Despite the explosion in e-scooters sharing services over the last two years, the success of the market has been overshadowed by the negative headlines, in the worst case prompting some cities to ban e-scooter's altogether. When we investigated the situation, we discovered that the 3 core problems contributing to a negative perception of the services:
1. Scooters litter our streets: In scooter-sharing neighborhoods, when rider reach their destination, they abandon their bikes and the resulting ‘clutter’ takes its toll.
Fallen scooters blocks sidewalks and driveways, neighborhood residents call in complaints and a person is sent out to move the bikes.
- How might we design a platform that helps up-right fallen scooters and park them in a safe zone?
- How might we design an interface to enable fleet managers to monitor and intervene when needed?
2. Geolocation Issue: Scooters are often located in areas of high demand such as train stations, college campuses, etc. In the day’s initial demand surge, scooters are rented and left at the destinations.
The GPS software doesn’t always find scooters left at random destinations. The end result: Within any given day, only one scooter of surge demand is addressed.
- How might we enable each scooter to drive itself to the nearest destination facing high demand?
3. Logistics Problem: Parking scooters in the morning are the biggest logistical problem companies are facing right now. A person who is loading & unloading scooters in the morning is always prone to injury which falls under company liability.
How might we design an interface that enables the scooter to park itself in the morning for consumer service?
The Solution:
- Scooter Valet: An intelligence platform that can upgrade any scooter-sharing service to include a suite of ‘smart’ services.
- Relocating & Rebalancing scooters: Self driving scooters to the nest that is nearest the surge in demand.
- Self-driving vision navigation: Combining autonomous technology with human intervention.
Personas
With the help of information architecture principles we able to form a skeleton for the web application that includes: Visual elements, functionality, interaction, and navigations
Prototype
Crafting wireframes and creating a beautiful user interface.A web application that enables users to control scooters remotely.
“One step back, three steps forward.”
Scooter Valet - a task is being created to activate the scooter to lift and park it next to another scooter or in a safe zone. This will be a physical, add-on device that turns any ‘dumb’ scooter into a ‘smart’ scooter.
Relocating & Rebalancing scooters without human touch-- With the help of vision navigation, the fleet manager can see through the camera feed and determine the actual location of the scooter. Then, the fleet manager can relocate the scooter to a visible place where users can access it with ease
Self-driving vision navigation: This feature makes use of the teleoperation functionality. Experience has shown that fleet managers working hand-in-hand with national and local authorities are the most effective way to integrate their services with existing transport infrastructure.
Testing
Solutions in hand, designers created wireframes. The sketches were ultimately turned into beautiful, user-friendly interfaces.
Our approach allowed us to:
Test and refine a new interface: While testing the interface, the user was confused about what to look and search for on the map. I modified the map by showing scooter locations and available battery life.
Visualize the structure clearly: The user didn’t like the visual aesthetic of the dashboard. Changes were made so that it's easy to see how many operators & vehicles are online, how many fleets and vehicles are registered. These changes were made to the dashboard so that it's easily understandable and readable.
Clarify the features of the interface: With the new interface, it was more clear to the operator which tasks to select without taking too much space from their screen.
Conclusion
After doing user testing, Jump Control web application is going through beta testing.