2022 Fiscal Year Final Research Report
Development of an evaluation method for urban planning using pedestrian data and transportation big data in the smart city era
| Project/Area Number |
20K14856
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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 | Osaka Institute of Technology (2021-2022)
Toyota Transportation Research Institute (2020) |
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Principal Investigator |
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| Project Period (FY) |
2020-04-01 – 2023-03-31
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| Keywords | まちづくり / 評価指標 / 評価手法 / 交通ビッグデータ / スマートシティ / COVID-19 / 公共交通サービス |
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| Outline of Final Research Achievements |
In order to strategically promote development in cities, an evaluating method for urban area is required, regardless Covid-19. We proposed an evaluation method using traffic big data and various analysis.
Specifically, we applied a topic model to extract features from a large amount of data and a Bayesian structural time series model that can express the effects of complex factors, using transportation big data such as pedestrian data, Wi-Fi packet sensor data, human flow data obtained from cell phone data, and parking lot usage data. We have shown that the effect of Covid-19 can be evaluated. In addition, it is showed that the relationship between urban activities, such as commercial sales, and traffic conditions, such as pedestrian traffic and car share, over a period of more than ten years.
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| Free Research Field |
都市交通計画，交通計画，都市・地域計画
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| Academic Significance and Societal Importance of the Research Achievements |
本研究の学術的意義として，交通ビッグデータを用いた都市の評価に適用可能な解析手段を示したことが挙げられる．Wi-Fiパケットセンサーデータにトピックモデルを適用した事例は過去に見られず，また，複数の交通ビッグデータにベイズ構造時系列モデルを適用する手法を提案し，都市の評価手法を新たに開発した．社会的意義としては，コロナ禍における都市の実態の分析結果から，コロナ禍により影響を受けやすい人々の活動や地域の特徴を示すとともに，コロナ禍における様々な経済活動に対する支援の必要性を示したことが挙げられる．また，人流が回復しても公共交通サービスが低下したままである実態を示したことは，特に重要な意義がある．
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