Personalizing public
transportation through AUI.

Personalizing public
transportation through AUI.

Proposed solution streamlines user interaction from 5 to 3 steps, enhancing satisfaction and efficiency.

Proposed solution streamlines user interaction from 5 to 3 steps, enhancing satisfaction and efficiency.

Challenge

Brainstorming apps that are used at least once a week and has potential to incorporate AUI to facilitate the user flow.

Tools

Figma, Research, Matchmaking

Duration

Fall 2023, 2 weeks.

Getting Started

What is Transit?

Transit app is a mobile application that provides real-time information about public transportation options in cities around the world. The app allows users to easily plan their route using various modes of transportation, including buses, trains, subways, and bikeshares.

Transit app is a mobile application that provides real-time information about public transportation options in cities around the world. The app allows users to easily plan their route using various modes of transportation, including buses, trains, subways, and bikeshares.

Concept Enactment

How does the implemented AUI work?

How does the implemented AUI work?

The Concept

Transit currently

The current Transit UI requires 5 steps for configuring a destination route regardless of where the user is headed.

The current Transit UI requires 5 steps for configuring a destination route regardless of where the user is headed.

Painpoints

Redundant user inputs from app launch to navigation.

Transit does not recognize repetition in patterns.

User is likely to be late by missing the best option.

When user is in a rush, friction points are amplified.

The Concept

Proposed AUI

The proposed AUI streamlines the process into 3 interactions, reducing friction from 5 steps. It saves time by simplifying route comparison. Users are alerted to the best route. Early notifications help users avoid missing their commute and being late.

What it aims to do

Notify the user before estimated arrival.

Prediction of potential destination and/or route.

Repair of inference errors when the prediction fails.

Suggestion of fastest transportation method.

01

Transit will notify users based on travel patterns.

Transit will notify users based on travel patterns

Notification based interactions

How does the implemented AUI work?

The AUI system will alert users based on their travel patterns, allowing them to check bus arrival times without unlocking their phones or accessing the Transit app.

02

On spotlight, Transit will recommend destinations

On spotlight, Transit will recommend destinations

Search / spotlight based interactions

Implementing a "easy Transit" option to allow users quickly add bus information based on AUI detection of past destinations.

Further prediction based on AUI scanning

But what if it gets my predicted destination wrong?

The AUI system will also offer anticipated destinations based on time and location, along with additional bus line details for each recommended destination.

03

In-app options to add specific bus information

In-app options to add specific bus information

A streamlined approach for accessing precise bus information without constant app navigation.

04

Implementation of visual queues

Implementation of visual queues

With this functionality, users can promptly estimate the distance of a bus visually.

The visualization will adjust colors based on the bus line.

Application of this AUI

Profitability

The visualization will adjust colors based on the bus line.

Value creation for user

Reduces friction in customer experience.

Increases user reliance on app for accuracy.

Saves valueable time for the app's users.

User is less likely to miss public transportation.

Revenue creation for partners & transit.

Increased user reliance on transit, leading to higher MAU and app usage frequency.

Improves user retention and subscription revenues for transit.

Increases in-app payments / revenues for partner agencies.

Potential to increase premium pricing in the long term with minimal impact on user volumes.

Application of this AUI

Return on investment

User Acceptance

Reduces friction from 5 steps to 3.

Saves time spent comparing routes.

Alerts user to the best route to destination.

Helps user avoid missing their commute with an early notification.

Financial Viability

Increases app retention and repeat payments for transport agencies and Transit.

Technical Viability

User travel history logs need to be stored, processed, and used to train the algorithm in order to provide adaptive predictions for users.

Sources of data include open APIs from transport agencies and real-time crowdsourced data.

Technical Viability

User travel history logs need to be stored, processed, and used to train the algorithm in order to provide adaptive predictions for users.

Sources of data include open APIs from transport agencies and real-time crowdsourced data.