IDEAS home Printed from https://ideas.repec.org/a/edt/jsserr/v12y2025i1p179-186.html
   My bibliography  Save this article

Artificial Intelligence: Exploring its Application in Transportation Industry

Author

Listed:
  • Augustus Orowhigo ATUBI

    (Department of Geography and Environmental Sustainability, Delta State University, Abraka, Nigeria)

Abstract

In modern transportation, technology continues to redefine what's possible. At the forefront of this revolution stands Al, a transformative force reshaping everything from logistics and safety to customer experience and efficiency. The robust growth of machine learning algorithms supported by various technologies like internet of things, robotic process automation, computer vision, natural language processing have enabled the growth of Al. In this paper, efforts are being made to explore some of the innovative Al technologies used in the transportation industry. The finding of this paper will not only increase the spate of utilization of artificial intelligence – enabled applications across the transportation industry but will also transform customer experience, introduce new tenses through which other stakeholders contribute to the growth and development of the transportation industry. To achieve this goal, this paper aims to explore existing areas of application of Al in the industry. Seven related keywords were used to carry out literature search across four (4) major databases, namely academia, google scholar, research gate and Scopus. Out of 1,694 articles accessed only 55 contained content relevant to this research. This study however, provided key overview of available literature on Al application in the transportation industry.

Suggested Citation

  • Augustus Orowhigo ATUBI, 2025. "Artificial Intelligence: Exploring its Application in Transportation Industry," Social Sciences and Education Research Review, Department of Communication, Journalism and Education Sciences, University of Craiova, vol. 12(1), pages 179-186, July.
  • Handle: RePEc:edt:jsserr:v:12:y:2025:i:1:p:179-186
    DOI: 10.5281/zenodo.15804536
    as

    Download full text from publisher

    File URL: https://sserr.ro/wp-content/uploads/2025/07/sserr-12-1-179-186.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.5281/zenodo.15804536?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Rusul Abduljabbar & Hussein Dia & Sohani Liyanage & Saeed Asadi Bagloee, 2019. "Applications of Artificial Intelligence in Transport: An Overview," Sustainability, MDPI, vol. 11(1), pages 1-24, January.
    2. Benjamin Maas, 2022. "Literature Review of Mobility as a Service," Sustainability, MDPI, vol. 14(14), pages 1-28, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tan Yigitcanlar & Kevin C. Desouza & Luke Butler & Farnoosh Roozkhosh, 2020. "Contributions and Risks of Artificial Intelligence (AI) in Building Smarter Cities: Insights from a Systematic Review of the Literature," Energies, MDPI, vol. 13(6), pages 1-38, March.
    2. Cohen-Blankshtain, Galit & Gofen, Anat, 2025. "Understanding voluntary carlessness: Why outliers matter," Journal of Transport Geography, Elsevier, vol. 123(C).
    3. Silvia Stuchi & Sonia Paulino & Faïz Gallouj, 2022. "Social Innovation in Active Mobility Public Services in the Megacity of Sao Paulo," Sustainability, MDPI, vol. 14(19), pages 1-16, September.
    4. Manuel Rey-Moreno & Rafael Periáñez-Cristóbal & Arturo Calvo-Mora, 2022. "Reflections on Sustainable Urban Mobility, Mobility as a Service (MaaS) and Adoption Models," IJERPH, MDPI, vol. 20(1), pages 1-14, December.
    5. Catarina N. S. Silva & Justas Dainys & Sean Simmons & Vincentas Vienožinskis & Asta Audzijonyte, 2022. "A Scalable Open-Source Framework for Machine Learning-Based Image Collection, Annotation and Classification: A Case Study for Automatic Fish Species Identification," Sustainability, MDPI, vol. 14(21), pages 1-13, November.
    6. Ghasri, Milad & Ardeshiri, Ali & Zhang, Xiang & Waller, S. Travis, 2024. "Analysing preferences for integrated micromobility and public transport systems: A hierarchical latent class approach considering taste heterogeneity and attribute non-attendance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    7. Wu, Min & Wang, Nanxi & Yuen, Kum Fai, 2023. "Can autonomy level and anthropomorphic characteristics affect public acceptance and trust towards shared autonomous vehicles?," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    8. Mochen Liao & Kai Lan & Yuan Yao, 2022. "Sustainability implications of artificial intelligence in the chemical industry: A conceptual framework," Journal of Industrial Ecology, Yale University, vol. 26(1), pages 164-182, February.
    9. Zulamir Hassani, Afdhal & Yusoff, Fazirah & Wan Zain, Wan Nor Aisyah, 2021. "Fair and Responsible in Logistics IR 4.0," MPRA Paper 108432, University Library of Munich, Germany.
    10. Marya Butt & Ander de Keijzer, 2022. "Using Transfer Learning to Train a Binary Classifier for Lorrca Ektacytometery Microscopic Images of Sickle Cells and Healthy Red Blood Cells," Data, MDPI, vol. 7(9), pages 1-21, September.
    11. Volodymyr N. Skoropad & Stevica Deđanski & Vladan Pantović & Zoran Injac & Slađana Vujičić & Marina Jovanović-Milenković & Boris Jevtić & Violeta Lukić-Vujadinović & Dejan Vidojević & Ištvan Bodolo, 2025. "Dynamic Traffic Flow Optimization Using Reinforcement Learning and Predictive Analytics: A Sustainable Approach to Improving Urban Mobility in the City of Belgrade," Sustainability, MDPI, vol. 17(8), pages 1-31, April.
    12. Sohani Liyanage & Hussein Dia & Rusul Abduljabbar & Saeed Asadi Bagloee, 2019. "Flexible Mobility On-Demand: An Environmental Scan," Sustainability, MDPI, vol. 11(5), pages 1-39, February.
    13. Smith, Göran & Sørensen, Claus Hedegaard, 2023. "Public-private MaaS: Unchallenged assumptions and issues of conflict in Sweden," Research in Transportation Economics, Elsevier, vol. 99(C).
    14. Xiaomin Zhou & Chaemoon Yoo & Xiyan Sun & Yingjie Lai & Younghwan Pan, 2022. "Pilot Study on User Service Guarantee Elements for Electric Minivans," Sustainability, MDPI, vol. 14(22), pages 1-20, November.
    15. Ye, Jianhong & Zheng, Jiaqi, 2024. "How stakeholders influence MaaS implementation? An analysis based on evolutionary game theory," Transport Policy, Elsevier, vol. 149(C), pages 198-210.
    16. Pamucar, Dragan & Deveci, Muhammet & Gokasar, Ilgin & Tavana, Madjid & Köppen, Mario, 2022. "A metaverse assessment model for sustainable transportation using ordinal priority approach and Aczel-Alsina norms," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    17. Antonella Franco & Antonino Vitetta, 2023. "Preference Model in the Context of Mobility as a Service: A Pilot Case Study," Sustainability, MDPI, vol. 15(6), pages 1-14, March.
    18. Jae-joon Chung & Hyun-Jung Kim, 2020. "An Automobile Environment Detection System Based on Deep Neural Network and its Implementation Using IoT-Enabled In-Vehicle Air Quality Sensors," Sustainability, MDPI, vol. 12(6), pages 1-17, March.
    19. Iria Lopez-Carreiro & Andres Monzon & Elena Lopez, 2023. "MaaS Implications in the Smart City: A Multi-Stakeholder Approach," Sustainability, MDPI, vol. 15(14), pages 1-27, July.
    20. McHardy, Jolian, 2024. "Platform business models and strategic price interaction," Transportation Research Part B: Methodological, Elsevier, vol. 182(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:edt:jsserr:v:12:y:2025:i:1:p:179-186. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dan Valeriu Voinea (email available below). General contact details of provider: http://cis01.central.ucv.ro/litere/cadr_juridic/departament_comunicare_jurnalism_stiinte_ale_educatiei/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.