Team Name

EcoCommute

Team Members

Project Description

Problem Statement

Currently, Victoria is facing a challenge in managing their urban mobility, mainly due to the increase in private vehicles over the years. This leads to increased traffic congestion, carbon emissions, bad air quality and an overall reduction of public transport.
Certain gaps in data related to demographics limit the ability to implement targeted solutions. The Victoria Government pledges to reduce their transport sector emissions. To achieve this goal a sustainable solution that reduces dependency on private vehicles is needed.

Project Description

Our project, Eco Commute aims to revolutionise urban mobility in Australia by taking Victoria as a starting point and creating an integrated, data-driven system that prioritises sustainable transport over private vehicles use.

We introduce MykiEarn, an app, which can be connected to your myki card. This app serves as an incentive award system where users can play a game to earn points and redeem discounts.
Moreover, this app can be used to store data which can help in filling the gap of inconsitent government data related to age group, distances travelled and locations ensuring privacy encryption.
To assess the impact of use of MykiEarn, we predict a increase by the year 2029. Conversely, the model shows a declination in the use of public transport without MykiEarn system.

Implementing this solutions, leverages the use of analysis, behavioural insights, ‘cutting-edge technology’ and innovative policies to build a connected urban environment where public transport, cycling, walking and electric mobility are the default modes for the citizens. It paves the way to create a more sustainable and liveable city in line with Victoria’s zero emissions goal by 2045.

Data Story

During our analysis, the team noticed significant gaps in the amount of data available to detect trends and patterns relating to public transport usage. There was no data relating to public transport travel before 2018 and it was not consistent after 2018. The data lacked accuracy to be sufficient to detect trends and patterns. Additionally, there was no data relating to age demographics and locations most likely travelled to when using public transport.

Our team analysed patterns and trends using the provided dataset however the gaps in data were quite significant and prevented more accurate analysis. Using the dataset relating to car registration, we uncovered increasing trends over the last twenty years. There was a slight decline during the COVID 19 pandemic, however this value picked up the years following the pandemic.

To compare this data in relation to the public transport data, our team constricted the car registration data to the years 2018 – 2024 and conducted the analysis. This data still shows the increase in car registrations, apart from the 2024 data which is not yet completed.

During the COVID 19 pandemic, there was a steady decline, and this decline has not increased to its original level. This could be a result of individuals working from home or preferring to use private cars over public transport.[2]

Our solutions, considering the trends relating to greater car registration in relation to decline in public transport usage, will attempt to encourage individuals to use their cars less and switch to public transport modes of travel.

1) MykiEarn as a mode of Data Collection

MykiEarn is one of the solutions that our team proposes to target identified gaps in data.

2) MykiEarn as an Incentive

MykiEarn was created to encourage a greater amount of individuals to use public transport and to keep using public transport.

3) MykiEarn as an Awareness Raising Tool

Additionally, MykiEarn can be used to raise awareness of health benefits to the general public through their access to our app.

4) High Occupancy Vehicle (HOV) Lanes

To tackle the problem of private car usage, our team proposes two solutions. One is to introduce High Occupancy Vehicle (HOV) lanes to encourage more people to drive to places in the same vehicle.

5) Community Challenge

The second solution was to introduce a community challenge, such as a “No Car Friday”, where individuals were asked to not drive their car on any given weekday as an effort to move to more sustainable modes of transport.

Predictions

We used a linear regression machine learning model to predict the future usage of public transport. Based on current trends, the model shows a significant downward trajectory in public transport usage if no interventions are made. However, when we introduced an incentive program like MykiEarn, the model predicted a positive shift, with public transport usage increasing over time. This highlights the potential impact of targeted incentives on reversing the decline and encouraging sustainable travel.