Data-Driven Optimization for Smart Urban Mobility

Topic Information

Dear Colleagues,

In the 21st century, rapid urbanization and smart city initiatives have contributed to sustainable and efficient mobility becoming a pressing priority. Data-driven optimization now plays a central role in addressing congestion, pollution, and accessibility challenges. By integrating big data analytics, IoT, and artificial intelligence, cities are reshaping transportation planning and real-time management, enabling smarter decisions and improved service delivery. Yet, these advances also raise issues of equity, implementation, and public acceptance. This Topic welcomes the submission of contributions regarding AI and data analytics in transport planning, smart mobility case studies, consumer behavior insights, sustainability impacts, and innovative public–private collaborations. Through interdisciplinary research and practice, we aim to explore strategies that ensure urban transport systems are not only intelligent, but also inclusive, resilient, and sustainable.

Prof. Dr. Zhijie Dong
Dr. Weike Lu
Dr. Tianqi Gu
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Electronics electronics	2.6	6.1	2012	16.8 Days	CHF 2400	Submit
Energies energies	3.2	7.3	2008	16.2 Days	CHF 2600	Submit
Future Transportation futuretransp	1.7	3.8	2021	33.4 Days	CHF 1200	Submit
Smart Cities smartcities	5.5	14.7	2018	26.8 Days	CHF 2000	Submit
Sustainability sustainability	3.3	7.7	2009	19.3 Days	CHF 2400	Submit

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