Assessing the Coordination of Electric Vehicle Adoption on Urban Energy Transition: A Geospatial Machine Learning Framework

• Project/Area Number: 24K20973
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 64060:Environmental policy and social systems-related
• Research Institution: Waseda University
• Principal Investigator: KANG JING 早稲田大学, 高等研究所, 講師(任期付) (60914223)
• Project Period (FY): 2024-04-01 – 2026-03-31
• Project Status: Granted (Fiscal Year 2024)
• Budget Amount: ¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000); Fiscal Year 2025: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000); Fiscal Year 2024: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
• Keywords: decarbonization / machine learning / GIS / spatial analysis / carbon neutrality

Outline of Research at the Start

The rise of electric mobility poses challenges like spatial imbalances and temporal conflicts in public charging networks. This study develops a novel empirical model integrating multiple datasets and interdisciplinary methods to enhance infrastructure efficiency and promote sustainable transition.