TY - JOUR
T1 - Global distribution and readiness status of artificial intelligence application on mobility projects
AU - Pandyaswargo, Andante Hadi
AU - Maghfiroh, Meilinda Fitriani Nur
AU - Onoda, Hiroshi
N1 - Funding Information:
This research is supported by (1) the New Energy and Industrial Technology Development Organization (NEDO), Japan , and (2) the Japan Society for the Promotion of Science (JSPS) Kakenhi grant project number JP21K17930 with a research theme: Addressing the sustainability challenges of off-grid renewable energy systems: Smart community reverse innovation.
Publisher Copyright:
© 2022 The Author(s)
PY - 2023/3
Y1 - 2023/3
N2 - The mobility sector is experiencing a global transition towards cleaner and more sustainable technologies. Many mobility projects are developing artificial intelligence (AI) technologies to improve the operational efficiency of mobility, such as charging system optimization for electric vehicles (EVs), autonomous driving, and traffic controls. This study presents such projects’ global distribution by showing a geographic information system (GIS)-generated map and analyzes the readiness level of those technologies by employing the Japanese Technology Readiness Assessment (J-TRA) methodology. The results show that most projects are located in Europe. Among the analyzed AI uses, the smart parking system and lane tracing assistance technologies have the highest level of readiness. Further training of AI to be fully compatible with the real operating environments and updates of traffic policies are necessary to allow advancement of the technology readiness of the rest of AI mobility technologies types.
AB - The mobility sector is experiencing a global transition towards cleaner and more sustainable technologies. Many mobility projects are developing artificial intelligence (AI) technologies to improve the operational efficiency of mobility, such as charging system optimization for electric vehicles (EVs), autonomous driving, and traffic controls. This study presents such projects’ global distribution by showing a geographic information system (GIS)-generated map and analyzes the readiness level of those technologies by employing the Japanese Technology Readiness Assessment (J-TRA) methodology. The results show that most projects are located in Europe. Among the analyzed AI uses, the smart parking system and lane tracing assistance technologies have the highest level of readiness. Further training of AI to be fully compatible with the real operating environments and updates of traffic policies are necessary to allow advancement of the technology readiness of the rest of AI mobility technologies types.
KW - Artificial intelligence
KW - Electric vehicle
KW - GIS
KW - TRA
KW - Technology readiness
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U2 - 10.1016/j.egyr.2022.11.070
DO - 10.1016/j.egyr.2022.11.070
M3 - Article
AN - SCOPUS:85141911726
SN - 2352-4847
VL - 9
SP - 720
EP - 727
JO - Energy Reports
JF - Energy Reports
ER -