Yasuda Shohei 安田昌平

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YASUDA SHOHEI 安田昌平

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Researcher Number	00899247
Affiliation (Current)	2025: 東京大学, 大学院工学系研究科(工学部), 助教
Affiliation (based on the past Project Information) *help	2021 – 2024: 東京大学, 大学院工学系研究科(工学部), 助教
Review Section/Research Field	Principal Investigator Basic Section 22050:Civil engineering plan and transportation engineering-related
Keywords	Principal Investigator 交通ネットワーク / 交通状態推定 / 深層学習 / 交通流理論 / 走行軌跡データ / 機械学習 / 交通工学 / グラフニューラルネットワーク / ニューラルネットワーク / kinematic wave理論 / ベイズ統計学 / 空間統計学 / ネットワーク表現

疎な観測に基づくネットワークの交通状態予測を目的とした交通流理論と深層学習の融合Principal Investigator
- Principal Investigator
  
  安田昌平
- Project Period (FY)
  2024 – 2027
- Research Category
  
  Grant-in-Aid for Early-Career Scientists
- Review Section
  
  Basic Section 22050:Civil engineering plan and transportation engineering-related
- Research Institution
  The University of Tokyo
Development of Real-Time Traffic State Estimation Methods for Next-Generation Traffic ControlPrincipal Investigator
- Principal Investigator
  
  YASUDA SHOHEI
- Project Period (FY)
  2021 – 2023
- Research Category
  
  Grant-in-Aid for Early-Career Scientists
- Review Section
  
  Basic Section 22050:Civil engineering plan and transportation engineering-related
- Research Institution
  The University of Tokyo

All 2024 2022

All Journal Article Presentation

[Journal Article] Trajectory Data-Driven Network Representation for Traffic State Prediction using Deep Learning2024
- Author(s)
  Yasuda Shohei、Katayama Hiroki、Nakanishi Wataru、Iryo Takamasa
- Journal Title
  
  International Journal of Intelligent Transportation Systems Research
  
  Volume: 22 Issue: 1 Pages: 136-145
- DOI
  10.1007/s13177-023-00383-z
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-23K17551, KAKENHI-PROJECT-21K14266, KAKENHI-PROJECT-20H02267, KAKENHI-PROJECT-23K26218
[Journal Article] Comparative Validation of Spatial Interpolation Methods for Traffic Density for Data-driven Travel-time Prediction2022
- Author(s)
  Katayama Hiroki、Yasuda Shohei、Fuse Takashi
- Journal Title
  
  International Journal of Intelligent Transportation Systems Research
  
  Volume: 20 Issue: 3 Pages: 830-837
- DOI
  10.1007/s13177-022-00326-0
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-21K14266
[Presentation] Traffic Density Based Travel-Time Prediction With GCN-LSTM2022
- Author(s)
  Katayama Hiroki, Yasuda Shohei, Fuse Takashi
- Organizer
  IEEE International Conference on Intelligent Transportation Systems
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-21K14266

1. 中西航

# of Collaborated Projects: 0 results

# of Collaborated Products: 1 results

Yasuda Shohei 安田昌平

YASUDA SHOHEI 安田昌平

Research Projects

Research Products

Co-Researchers

疎な観測に基づくネットワークの交通状態予測を目的とした交通流理論と深層学習の融合Principal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Development of Real-Time Traffic State Estimation Methods for Next-Generation Traffic ControlPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

[Journal Article] Trajectory Data-Driven Network Representation for Traffic State Prediction using Deep Learning2024

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Comparative Validation of Spatial Interpolation Methods for Traffic Density for Data-driven Travel-time Prediction2022

Author(s)

Journal Title

DOI

Data Source

[Presentation] Traffic Density Based Travel-Time Prediction With GCN-LSTM2022

Author(s)

Organizer

Data Source

Yasuda Shohei 安田 昌平

YASUDA SHOHEI 安田 昌平

Research Projects

Research Products

Co-Researchers

疎な観測に基づくネットワークの交通状態予測を目的とした交通流理論と深層学習の融合Principal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Development of Real-Time Traffic State Estimation Methods for Next-Generation Traffic ControlPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

[Journal Article] Trajectory Data-Driven Network Representation for Traffic State Prediction using Deep Learning2024

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Comparative Validation of Spatial Interpolation Methods for Traffic Density for Data-driven Travel-time Prediction2022

Author(s)

Journal Title

DOI

Data Source

[Presentation] Traffic Density Based Travel-Time Prediction With GCN-LSTM2022

Author(s)

Organizer

Data Source

Yasuda Shohei 安田昌平

YASUDA SHOHEI 安田昌平