Built environment and public electric vehicle charging: an investigation using POI data and computer vision

Public Transport, Journal Year: 2025, Volume and Issue: unknown

Published: March 4, 2025

Language: Английский

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Forecasting of New Energy Vehicle Sales and Evaluation of Regional Development Based on BP Neural Network and EWM-TOPSIS

Highlights in Business Economics and Management, Journal Year: 2025, Volume and Issue: 53, P. 97 - 110

Published: March 17, 2025

This paper focuses on the new energy vehicle market, utilizing big data technology and artificial intelligence algorithms to perform statistics, analysis, forecasting in both temporal spatial dimensions. In time dimension, sales volume is forecasted by piecewise cubic Hermite interpolation, polynomial fitting, ARIMA model BP neural network model, results between different models are compared analyzed. Meanwhile, factors affecting this market analyzed using entropy weight method. development level of each province assessed TOPSIS comprehensive evaluation method, stage which provinces located classified K-means cluster analysis. The show that developing rapidly, but there still problem uneven some regions. At same time, study also found has higher credibility prediction, method EWM-TOPSIS can effectively assess city, analysis intuitively differences stage. research provide technical support theoretical for industrial China's era data.

Language: Английский

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Toward an equitable transportation electrification plan: Measuring public electric vehicle charging station access disparities in Austin, Texas

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(9), P. e0309302 - e0309302

Published: Sept. 5, 2024

The deployment of public electric vehicle charging stations (EVCS) is a critical component transportation electrification. Recent studies have highlighted growing concerns about disparities in accessibility to chargers between different demographic groups. This research expands ongoing equity by contextualizing existing discourse and analyzing charger access Austin, Texas. Using threshold toolkits, we investigated EVCS disparity across races income We conducted generalized additive model regression measure visualize the effects possible determinants on access. analysis results revealed that exists with most being installed areas where majority population Non-Hispanic White. There was more equal distribution EVCSs quartiles when compared race. However, middle- high-income groups had better than lower-income communities terms distance nearest EVCSs. Our found regional socio-demographic factors, such as race income, statistically significant impact also Austin’s current seems favor above poverty level higher numbers registered vehicles. Local policymakers should reflect findings this study develop an equitable electrification plan. Federal environmental justice plans Justice40 initiative can benefit from incorporating local contexts invest disadvantaged communities.

Language: Английский

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Who owns Electric Vehicles (EVs)? The relationship between EV adoption and socio-demographic characteristics across different price segments and brands in the Texas triangle

Research in Transportation Business & Management, Journal Year: 2024, Volume and Issue: 57, P. 101225 - 101225

Published: Oct. 16, 2024

Language: Английский

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