| Project/Area Number |
22K14339
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 22050:Civil engineering plan and transportation engineering-related
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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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| Project Status |
Granted (Fiscal Year 2023)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2023: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2022: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | Transportation Planning / Machine Learning / ICT / Emissions / Randomized Control Trial |
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| Outline of Research at the Start |
The goals of the research will be achieved through two objectives. The first objective of the research is to develop an ICT platform that implements an ethical, attractive, and personalized algorithm that will prioritize the reduction of CO2 emissions. The ICT platform will provide users with a choice between the novel algorithm and traditional algorithms (such as profit maximization and travel time reduction). The second objective of the research is to conduct a randomized control trial in Higashihiroshima to quantitatively evaluate the adoption and effectiveness of the ICT platform.
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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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