Significance of artificial intelligence in the development of sustainable transportation
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2023.14.2.28Keywords:
Artificial Intelligence, Development, Sustainable development goals, Sustainable transportation, Transport.Dimensions Badge
Issue
Section
License
Copyright (c) 2023 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The idea of Sustainable development has gained more attention since it involves satisfying needs without degrading the environment. Sustainable development has many targets across various subjects in which Sustainable Transportation is one of the cores to sustainable development. The objective of sustainable transportation is to achieve social, environmental and economic growth with universal access, enhanced safety, improved resilience and infrastructure, reduction of emission in greenhouse gases, traffic management, freight management by different modes of transportation. It is vital and interlinked across several sustainable development goals (SDGs) and targets in the 2030 Agenda proposed by United Nations. There is a need to improve sustainable transportation, which can be achieved through artificial intelligence as it helps the sector to increase public transport, traffic safety, reduce accidents and improve traffic management, decrease carbon emissions, rise reliability and also leverage economic growth through methods like Fuzzy logic (FL), Artificial Neural Networks, Ant Colony Optimiser, Genetic algorithms, Swarm optimization algorithm, Simulated Annealing. It is also supported by Big Data Analysis, Internet of Things, Robotic process Automation. This paper addresses the overview of the importance of sustainable transportation along with the role of artificial intelligence in different modes of transportation, current level of sustainability across globe, progress in transport system and conclude with challenges and future improvements that can be made towards the goal.Abstract
How to Cite
Downloads
Similar Articles
- P. J. Robinson, S. W. A. Prakash, Stochastic artificial neural network for magdm problem solving in intuitionistic fuzzy environment , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Vinodini R, Ritha W, Sasitharan Nagapan, The green inventory model for sustainable environment that includes degrading products and backordering with integration of environmental cost , The Scientific Temper: Vol. 16 No. 08 (2025): The Scientific Temper
- U. Johns Praveena, J. Merline Vinotha, Bilevel Fractional/Quadratic Green Transshipment Problem by Implementing AI traffic control system with Multi Choice Parameters Under Fuzzy Environment , The Scientific Temper: Vol. 16 No. 11 (2025): The Scientific Temper
- Gurpreet S. Saund, Kulandai Samy, Eco-critical dystopia and anthropocentrism in Margaret Atwood’s Oryx and Crake , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Sowmiya M, Banu Rekha B, Malar E, Ensemble classifiers with hybrid feature selection approach for diagnosis of coronary artery disease , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- P S Renjeni, B Senthilkumaran, Ramalingam Sugumar, L. Jaya Singh Dhas, Gaussian kernelized transformer learning model for brain tumor risk factor identification and disease diagnosis , The Scientific Temper: Vol. 16 No. 02 (2025): The Scientific Temper
- Temesgen Asfaw, Customer churn prediction using machine-learning techniques in the case of commercial bank of Ethiopia , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Pankitbhai C. Patel, Jignesh Valand, A study on consumer’s perception towards e-banking services of co-operative banks in rural areas with special reference to Gandhinagar , The Scientific Temper: Vol. 16 No. 05 (2025): The Scientific Temper
- Bhaskar Pandya, Pradipsinh Zala, Vocational education and lifelong learning: Preparing a skilled workforce for the future , The Scientific Temper: Vol. 15 No. spl-2 (2024): The Scientific Temper
- Manisha Anil Vhora, Vidya Bhandwalkar, Prashant Mangesh Rege, AI-driven HR analytics: Enhancing decision-making in workforce planning , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
<< < 4 5 6 7 8 9 10 11 12 13 > >>
You may also start an advanced similarity search for this article.

