Journal of Advanced Transportation

Artificial Intelligence Approaches for Green Transportation Planning

Publishing date
01 Jul 2022
Submission deadline
18 Feb 2022

1University of Twente, Enschede, Netherlands

2Universidad de Los Andes, Santiago de Chile, Chile

3University Federico Santa María, Valparaíso, Chile

4Delft University of Technology, Delft, Netherlands

This issue is now closed for submissions.
More articles will be published in the near future.

Artificial Intelligence Approaches for Green Transportation Planning

This issue is now closed for submissions.
More articles will be published in the near future.


Green and environmentally transport planning is a current challenge for public and private organizations. There is a demand for implementing innovative and advanced transport solutions to reduce environmental and social impacts within operations. In this context, current trends are calling for the incorporation of novel strategies and approaches in transport systems for reducing energy usage as well as waste and pollution generation. The consideration of that goal and the connection to this green dimension leads to the need of developing and reviewing current models and methods in the light of modern transport solutions and technologies (e.g., energy reuse, alternative fuels, hybrid and green-energy based vehicles, collaborative planning, autonomous vehicles and truck platooning).

Solutions, approaches, and methodologies can assist managers and decision-makers in the design and development of transportation systems while jointly considering environmental-related advances. Research can be furthered by advancing the way we collect, process, and use data within quantitative and decision support approaches. Furthermore, with new smart transport technologies and artificial intelligence (e.g., machine learning, meta-learning, etc.), significant effects can be obtained. To properly capture and utilize the full potential of the latest developments, it is necessary to consider and analyze how artificial intelligence (AI) approaches and decision support systems can jointly foster efficient and environmentally friendly transport operations.

The aim of this Special Issue is to highlight the current progress of artificial intelligence approaches for designing, developing, and promoting green and sustainable transportation systems through optimization, intelligent use of data, and advanced decision support. This Issue will aim to provide a platform of research exploring and dealing with transportation problems within the interplay between transportation planning, design, and operations. Submissions should incorporate advanced transport technologies and artificial intelligence techniques that support and enhance transport planning, promote green development, and mitigate negative environmental impacts.

Potential topics include but are not limited to the following:

  • AI techniques for green transport planning
  • Quantitative evaluation of green transportation systems
  • Theoretical and/or empirical analysis of AI approaches in green transportation
  • AI techniques for online and offline planning
  • AI and mathematical programming in green transportation planning
  • Sustainability in green transportation systems using AI
  • The use of AI and operations research to address sustainable planning
  • Data-driven planning approaches considering environmental-related features
  • Smart transport solutions using AI to reduce environmental impacts
  • Emerging transport technologies to support synchromodal transport network planning
  • Heuristics, meta-heuristics, and hyper-heuristics-based systems
  • Integrating real-time information into the optimization frameworks
  • Transportation approaches with shared infrastructure and resources
Journal of Advanced Transportation
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Article of the Year Award: Outstanding research contributions of 2021, as selected by our Chief Editors. Read the winning articles.