Prediction of new energy vehicles ownership with PCA-logistic model under peak carbon dioxide emissions and carbon neutrality

Guoyi Tang; Jie Shao; Xinxin Yu; Jianhua Gao

doi:10.1117/12.2652489

21 November 2022 Prediction of new energy vehicles ownership with PCA-logistic model under peak carbon dioxide emissions and carbon neutrality

Guoyi Tang, Jie Shao, Xinxin Yu, Jianhua Gao

Author Affiliations +

Proceedings Volume 12340, International Conference on Frontiers of Traffic and Transportation Engineering (FTTE 2022); 123400B (2022) https://doi.org/10.1117/12.2652489
Event: International Conference on Frontiers of Traffic and Transportation Engineering (FTTE 2022), 2022, Lanzhou, China

Abstract

New energy vehicles play a pivotal role in the realization of carbon peak and carbon neutrality. The prediction of the ownership of new energy vehicles is of great significance to realize the goal of environmental protection in transportation field. The fluctuations of new energy vehicle ownership data follow a long-term nonlinear trend influenced by complex impact factors where nonlinear relationships are in between. Therefore, it is important to use reasonable and accurate methods to analyze and forecast the new energy vehicle ownership to facilitate the rational formulation of policies. In order to study the change of vehicle ownership under the influence of multiple factors such as GDP, urbanization rate and highway mileage, the method of combining principal component factor analysis and logistic nonlinear model is adopted. The result shows that the nonlinear logistic regression curve obtained has a higher fitting degree with the actual data. According to the industry planning, the number of new energy vehicles in 2035 is about 156 million.

Citation Download Citation

Guoyi Tang, Jie Shao, Xinxin Yu, and Jianhua Gao "Prediction of new energy vehicles ownership with PCA-logistic model under peak carbon dioxide emissions and carbon neutrality", Proc. SPIE 12340, International Conference on Frontiers of Traffic and Transportation Engineering (FTTE 2022), 123400B (21 November 2022); https://doi.org/10.1117/12.2652489

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available