Team Name:
Fantastic Four
Team Members:
Fantastic Four
In the quest for a sustainable future, nations around the world are taking bold steps toward reducing their carbon footprint. Australia, too, is embracing change. With a resolute commitment to achieving net-zero emissions, Australia is exploring innovative strategies to take on the role. One such strategy is the widespread adoption of electric vehicles (EVs), where the uptake is targeted towards 50% by 2023. We did an evaluation to understand the current state of EV adoption. Compared to the total number of vehicles, the figures for EVs increase faster, especially after the pandemic. However, based on the 2023 Quarter 2 vehicle registration statistics from Data.Vic, there is only 0.6% of the vehicle registered are EVs (34,407 vs 5,602,616). To accelerate the process, an essential question lingers - what factors truly drive people to adopt EVs?
By meticulously analyzing various census data sources, including the 2023 Q2 dataset that contains the count of all vehicles registered in Victoria and 2021 ABS census data for Victoria, we compare the number of registered EVs in different postcodes with the census data in these postcodes.
We generated the correlation coefficient for EV number and the census data, thus a clear picture began to emerge.
Armed with this knowledge, the EV industry and government agencies can strategically harness these factors to drive higher EV adoption rates.
Empowering Tomorrow, Electrifying Today.
Our datasets are mainly from the 2021 ABS census (link:https://www.abs.gov.au/census/find-census-data/datapacks?release=2021&product=GCP&geography=POA&header=S) and Data.Vic (link= https://discover.data.vic.gov.au/dataset/whole-fleet-vehicle-registration-snapshot-by-postcode and link:https://discover.data.vic.gov.au/dataset/monthly-new-vehicle-registrations).
Due to the lack of types of new vehicles registered from 2018 to 2022 in Victoria, Australia, we do not have the exact number of new EVs each year. However, Tesla is the car manufacturer that makes only EVs, so we delved into the data from Tesla as a representation to show the trend.
By processing the dataset from Data.Vic that contains the count of new vehicle registrations,
we observed a growth in the adoption of (Tesla) EVs except for 2022 due to the pandemic. We compare the EV registration in different postcodes and calculated the correlation coefficient (cc) to find the relation between EV uptakes and the features in each postcode. cc is a number between [-1, 1], the more it is close to 1 means the stronger positive effect is, and vice versa. We would like to put eyes on the largest cc features as well as the smallest cc.
We normalize each feature to [0, 1] and adjust the EV number in each postcode based on their population.
Using the cc, we have found many interesting observation.
Description of Use We use it to find out the EV registration trend and total vehicle trend from 2018 to 2022
Description of Use We use it to find out the features that could affect the EV uptakes.
Description of Use We use it to find out the new EV registration number by year.
Eligibility: Use at least 1 dataset from Data.Vic list.
Go to Challenge | 12 teams have entered this challenge.
