CYCLECITY

XIYUAN

Dashboard for Cycling facilities planning

Type

Year

Key Words

Design In University

2022

UI/UX Dashboard Data Visualization

Dashboard for Cycling facilities planning

CYCLECIT is a dashboard designed to assist stakeholders such as public transport companies and municipalities in enhancing the city’s cycling rate. It offers features like monitoring cycling rates and planning new cycle lanes or facilities based on the specific conditions of different areas.

I completed CYCLECITY during my ENVISIONING AI THROUGH DESIGN studio at Politecnico di Milano. The course taught us how to work with data and AI models to create dashboard designs. I played a major role in exploring the AI model, creating wireframes, and contributing to the UI design.a

Abour the course...

Each group was assigned a stakeholder, and ours was a public transport company. Our goal was to identify the problems and opportunities that arose during the pandemic and propose a dashboard solution with embodied AI system to the company’s manager.

Given the accessibility of the database and research, our team chose London as our target city and Transport for London (TFL) as our specific company. The manager of TFL served as our stakeholder.

How Might We

Help TFL leverage the pandemic as an opportunity to increase cycling and promote sustainable transportation?

Value Proposition

Dashboard Design

Methodology

Based on the insights from the research on TfL and its manager, we applied User Stories to interpret the core functionality of the software, as a way to clarify how the software features provide value to the client. Through the User Stories, we iterated and defined the information architecture and applied Scrum and Agile approach to break the development process into 5 sprints based on the user stories and the new information architecture. For each Sprint, concepts are developed and iterated through a process of Benchmarking – Wireframing – Peer Reviewing & A/B Testing.

User Stories

In the user story, we describe two main areas of interaction that users can have with the dashboard: one without AI involvement, i.e. visualizing the underlying data to understand the current status of different zones, and the other with AI involvement, i.e. clustering the underlying data and analyzing its impact to give users investment recommendations.