| 研究課題/領域番号 |
22K14339
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| 研究種目 |
若手研究
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| 配分区分 | 基金 |
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| 審査区分 |
小区分22050:土木計画学および交通工学関連
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| 研究機関 | 広島大学 |
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研究代表者 |
VARGHESE VARUN 広島大学, 先進理工系科学研究科(国), 助教 (40834718)
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| 研究期間 (年度) |
2022-04-01 – 2025-03-31
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| 研究課題ステータス |
交付 (2023年度)
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| 配分額 *注記 |
4,420千円 (直接経費: 3,400千円、間接経費: 1,020千円)
2023年度: 2,730千円 (直接経費: 2,100千円、間接経費: 630千円)
2022年度: 1,690千円 (直接経費: 1,300千円、間接経費: 390千円)
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| キーワード | Transportation Planning / Machine Learning / ICT / Emissions / Randomized Control Trial |
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| 研究開始時の研究の概要 |
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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| 研究実績の概要 |
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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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
3: やや遅れている
理由
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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| 今後の研究の推進方策 |
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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