Identifying of gpt-4’s abilities in the context of transportation planning in Sri Lanka

dc.contributor.authorWanniarachchi, S
dc.contributor.authorJayasinghe, A
dc.contributor.editorGunaruwan, TL
dc.date.accessioned2023-10-12T06:43:42Z
dc.date.available2023-10-12T06:43:42Z
dc.date.issued2023-08-26
dc.description.abstractThe study aims to investigate the capabilities of GPT-4, a cutting-edge large language model developed by OpenAI, in the context of transportation planning in Sri Lanka. This research delves into three main sectors: transport planning knowledge, concepts, and strategies; technical-oriented data, methodologies, and tools; and stakeholders' opinions. The study examines GPT-4's ability to articulate transport planning concepts and methods, providing creative policies adapted to Sri Lanka's specific challenges using a thorough approach. The model's capacity to provide methods for data analysis using Geographic Information Systems (GIS) applications is also investigated. The findings reveal that GPT-4 demonstrates outstanding capabilities in proposing practical transportation strategies and policies, akin to those presented by experienced planners. Additionally, it shows a high level of proficiency in technical data processing, expediting the decision-making process. Despite acknowledging its drawbacks, the GPT-4 needs to be improved using Sri Lanka-specific domain information in order to improve contextual knowledge and provide accurate results. Understanding the influence of training data and sourcing relevant information is crucial for specialized applications like transportation planning. Planners must be aware of GPT-4's limitations, particularly in detecting hallucinations that simulate coherent responses. Human planners should maintain their role as critical decision-makers, leveraging AI tools like GPT-4 while continuing to invest in competencies, cross-domain knowledge, and data analysis proficiency. Striking this balance ensures effective collaboration in the transportation planning process.en_US
dc.identifier.citation**en_US
dc.identifier.conferenceResearch for Transport and Logistics Industry Proceedings of the 8th International Conferenceen_US
dc.identifier.departmentDepartment of Transport and Logistics Managementen_US
dc.identifier.emailsahansashi96@gmail.comen_US
dc.identifier.emailamilabj@uom.lken_US
dc.identifier.facultyEngineeringen_US
dc.identifier.pgnospp. 193-195en_US
dc.identifier.placeMoratuwa, Sri Lankaen_US
dc.identifier.proceedingProceedings of the International Conference on Research for Transport and Logistics Industryen_US
dc.identifier.urihttp://dl.lib.uom.lk/handle/123/21557
dc.identifier.year2023en_US
dc.language.isoenen_US
dc.publisherSri Lanka Society of Transport and Logisticsen_US
dc.relation.urihttps://slstl.lk/r4tli-2023/en_US
dc.subjectLarge language modelsen_US
dc.subjectGPT-4en_US
dc.subjectTransport planningen_US
dc.subjectSri Lankaen_US
dc.subjectplanning competencyen_US
dc.titleIdentifying of gpt-4’s abilities in the context of transportation planning in Sri Lankaen_US
dc.typeConference-Full-texten_US

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