by: Yeqian He, Jin Yang, Renjie Hu, Conghui Zhu
I. Introduction & Objective
Ride-hailing services like Uber rely on efficient pick-up location selection and indoor navigation for an optimal user experience. However, multi-level environments such as airports, train stations, and shopping malls pose challenges, leading to confusion and delays. GPS functionality is often limited indoors, further complicating navigation.
This study aims to enhance Uber’s pick-up system by introducing floor selection, improved visual navigation cues, and real-time estimated pick-up times. Our objective is to provide a seamless and intuitive user experience, reducing errors and optimizing ride-hailing efficiency.
The key research questions guiding this study are:
- How can Uber’s pick-up experience be improved in multi-level environments?
- What impact do floor selection and enhanced visual navigation have on usability?
- How does estimated pick-up time affect user decision-making?
II. Journey Maps & Interview
Competitive Analysis
We analyzed Uber alongside competitors Bolt and Gaode Maps (Amap) to identify strengths and weaknesses in pick-up selection and indoor navigation.
- Uber: Provides flexible pick-up point selection but lacks dedicated indoor navigation features. Users cannot explicitly select floors, leading to confusion in multi-level locations. Estimated arrival times are displayed but without precise contextual guidance.
- Bolt: Offers precise pick-up points but lacks advanced indoor navigation. No explicit floor selection is available, and estimated arrival times lack additional navigation context.
- Gaode Maps (Amap): Features strong indoor navigation with detailed floor mapping. Provides real-time estimated arrival times for various pick-up locations. However, it lacks ride-hailing service integration at Uber’s level.
III. Research Methodology
3.1 Tools Used
- Figma: UI/UX design prototyping(link).
3.2 User Testing & Survey Implementation
Two rounds of surveys were conducted before and after prototype testing, involving 16 participants:
- Pre-Prototype Survey: Focused on existing Uber experiences, challenges in pick-up selection, and user expectations.
- Post-Prototype Survey: Evaluated user satisfaction, ease of use, and efficiency improvements after testing the new interface.
IV. Results & Findings
4.1 Results
In the comparison between the before and after, we can see there are significant improvements in our prototype. In the original design, even though 90% of users had prior experience, they still could not find the boarding point. However, in our improved version, many users felt that the changes we made were much more necessary.
4.2 Key Findings
- Floor selection reduced user confusion and improved navigation efficiency.
- 85% of users found the green upward indicator intuitive.
- Users reported 40% fewer errors in pick-up selection with floor indication.
- A 50% increase in user satisfaction was observed post-prototype testing.
- 75% of users found estimated pick-up time helpful in decision-making.
4.3 User Feedback
- Users felt that estimated pick-up times for alternative locations should be displayed.
- The green dots indicating floor levels did not clearly specify stair/elevator direction.
- The floor display in the bottom-right corner was unclear about whether it represented the user’s current or target floor.
V. Insights & Future Improvements
5.1 Strengths
- Users found floor selection and estimated time display intuitive.
- Predefined pick-up locations helped reduce errors.
- Navigation cues improved usability in multi-level environments.
5.2 Areas for Improvement
- Display estimated pick-up times for alternative locations.
- Improve clarity in visual markers for stairs, elevators, and direction.
- Clearly differentiate the user’s current floor from the target pick-up floor.
5.3 Next Steps
- Implement real-time indoor positioning for dynamic guidance.
- Improve differentiation between multiple elevators and staircases.
- Expand testing to train stations and shopping malls.
- Enhance estimated time calculation with real-time movement tracking.
VI. Conclusion
This study identified key pain points in Uber’s pick-up selection and indoor navigation, leading to targeted improvements in floor selection, navigation cues, and estimated time display. The proposed enhancements significantly improve user efficiency and reduce confusion in multi-level locations. Future iterations should focus on refining indoor positioning and addressing additional user feedback to optimize the ride-hailing experience further.