MIMS Final Project 2020

Sweep Smart

Team members:

Advisor:

The Problem

The Department of Transportation (DOT) of the City of Oakland oversees the parking violation management of the city. DOT aims to manage parking in ways that achieve the City of Oakland’s overarching goals for economic growth, environmental responsibility, and social equity. Over the past years, street sweeping parking violations have contributed to more than 50% of the citations issued. The city and DOT would like to understand how to better manage street sweeping to minimize interruption to the local community and maximize the efficient use of a public resource.

The Goals

Sweep Smart is a street sweeping digitization and optimization tool for the city of Oakland. By utilizing the team’s background in machine learning, data science, data visualization, user research, and product design, the tool aims to integrate historical data of parking violations and parking space occupancy to recommend street sweeping routes and schedules to minimize potential street sweeping associated parking violations. We aim to:

Create a clean and organized environment for residents while minimizing interruption to the local community
Enhance operational efficiency of City of Oakland
Build useful and trustworthy technology to serve people and society

The Users and Their Painpoints

The primary users as well as the key stakeholders during our user research and design feedback iterations are:

Residents of the City of Oakland
Street Sweeping Planners, Supervisors and Operators
Transportation Department Planners and Operators

Based on several rounds of user research conducted with different groups of stakeholders, we have identified the following major pain points:

The Solutions

Based on the pain points, we conducted a couple of design thinking workshops and narrowed down our ideas. We developed low fidelity prototypes of our ideas and test them with real users. After several rounds of feedback and iterations, we decided to approach the problem from 3 different aspects.

The Plan

Our project plan includes the following steps:

User Research
Process Research and Historic Data Gathering
User Flow and Interface Design
Optimization Model Development
System Development

The Results

In mid-February 2020, we presented our Route Optimization Plan to the officials of the city of Oakland and received really positive feedback for the extensive insights and actionable recommendations we provided.

By the beginning of May, we successfully delivered a working sweep smart app and the website. For more details, please visit us at https://sweepsmart.github.io/ or see a demo in the attachment.