Exploring Commuting Characteristics and Regional Differences of New Energy Vehicles in the Guangdong–Hong Kong–Macao Greater Bay Area Based on ETC Big Data Exploring Commuting Characteristics and Regional Differences of New Energy Vehicles in the Guangdong–Hong Kong–Macao Greater Bay Area Based on ETC Big Data

• Published in: Applied spatial analysis and policy Vol. 18; no. 2
• Main Authors: Huang, Junda, Wen, Huiying, Huang, Kunhuo
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.06.2025; Springer Nature B.V
• Subjects: Alternative fuel vehicles; Big Data; Cluster analysis; Commuting; Electric vehicles; Energy; Human Geography; Landscape/Regional and Urban Planning; Metropolitan areas; Mobility; Regional differences; Regional/Spatial Science; Roads & highways; Social Sciences; Toll roads; Transport costs; Urban planning; Hong Kong China; China; Macao; K-means; Visualization; ETC Data; Commuting Vehicle Identification; New Energy Vehicles
• ISSN: 1874-463X; 1874-4621
• DOI: 10.1007/s12061-025-09659-1

The widespread adoption of electric vehicles has significantly reduced residents’ transportation costs and is gradually reshaping urban mobility patterns. As one of the world’s four major bay areas, the Guangdong-Hong Kong-Macao Greater Bay Area offers a unique opportunity to identify and analyze new energy vehicles commuting via its highways. This study focuses on these vehicles by leveraging extensive big data from highway Electronic Toll Collection (ETC) systems. We employed the K-means +  + clustering algorithm to perform a comprehensive cluster analysis of vehicles within the study area, thereby identifying potential commuter vehicles and visualizing their commuting patterns and hotspots. These findings provide valuable insights for urban planners regarding the daily variations in travel demand among new energy commuters in metropolitan areas. The key findings are as follows: 1) Approximately 7.13% of the total new energy small passenger vehicles in the Greater Bay Area are potential commuter vehicles, predominantly concentrated in Shenzhen, Guangzhou, and Foshan. 2) There are notable regional differences in the types of new energy commuter vehicles; for instance, Guangzhou and Foshan tend to favor pure electric vehicles for commuting, whereas Shenzhen exhibits a different trend. 3) Among new energy commuter vehicles, 81.42% of trips are intra-city, primarily within Shenzhen, Guangzhou, and Foshan; while only 18.58% are inter-city, predominantly occurring between Shenzhen-Dongguan, Huizhou-Shenzhen, and Foshan-Guangzhou.