2023 Fiscal Year Research-status Report
Development of an environmentally friendly ICT platform for transport management and analysis of user preferences
| Project/Area Number |
22K14339
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| Research Institution | Hiroshima University |
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Principal Investigator |
VARGHESE VARUN 広島大学, 先進理工系科学研究科(国), 助教 (40834718)
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| Project Period (FY) |
2022-04-01 – 2025-03-31
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| Keywords | Transportation Planning / Machine Learning / ICT / Emissions / Randomized Control Trial |
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| Outline of Annual Research Achievements |
The project in the fiscal year of 2023 focused on analyzing the existing data on how users respond to incentives and how does attitude play a role influencing environmentally conscious decisions.
As a part of this study previously collected GPS-based travel survey data was collected to see how changing GPS data collection frequencies impact mode detection accuracy and the interpretability of results. The results of this study were presented in the the 103rd TRB Annual Meeting held at Washington D.C. in January 2024.
Additionally, the spatial transferability of graph computation based discrete choice models were evaluated with the incentive dataset.
Additionally, a comprehensive review of the literature was done on randomized control trials applied in travel behavioral research.
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| Current Status of Research Progress |
Current Status of Research Progress
3: Progress in research has been slightly delayed.
Reason
The study has multiple components and primarily, the design and development of the algorithm for the ICT platform needed more time than initially anticipated.
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| Strategy for Future Research Activity |
Currently, I am performing a thorough review to understand the optimization methods used in previous personalization based studies. Following that, the next step would be to develop the novel algorithm for the ICT platform and then integrating that within the platform. Once that is done, I aim to utilize the platform for a pilot data collection exercise.
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| Causes of Carryover |
The preliminary work related to the development basic models, literature review, and analysis of secondary data took more time than expected. Therefore, the expenses could not be fully utilized in 2023. In 2024, the remaining amount will be used for the development of the algorithm, platform, and for the pilot testing.
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