Journal article icon

Journal article

Spatially disaggregated car ownership prediction using deep neural networks

Abstract:

Predicting car ownership patterns at high spatial resolution is key to understanding pathways for decarbonisation—via electrification and demand reduction—of the private vehicle fleet. As the factors widely understood to influence car ownership are highly interdependent, linearised regression models, which dominate previous work on spatially explicit car ownership modelling in the UK, have shortcomings in accurately predicting the relationship. This paper presents predictions of spatially dis...

Expand abstract
Publication status:
Published
Peer review status:
Peer reviewed

Actions


Access Document


Files:
Publisher copy:
10.3390/futuretransp1010008

Authors


More by this author
Institution:
University of Oxford
Division:
SSD
Department:
SOGE
Sub department:
Environmental Change Institute
Role:
Author
ORCID:
0000-0001-8930-805X
Publisher:
MDPI Publisher's website
Journal:
Future Transportation Journal website
Volume:
1
Issue:
1
Pages:
113-133
Publication date:
2021-06-20
Acceptance date:
2021-06-15
DOI:
EISSN:
2673-7590
Language:
English
Keywords:
Pubs id:
1182089
Local pid:
pubs:1182089
Deposit date:
2021-06-15

Terms of use


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP