UFRL
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Address: 2-1-6, Etchujima, Koto-ku, Tokyo, #135-8533, JAPAN
e-mail: tsakai2@kaiyodai.ac.jp -
NEWS
RESEARCH
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Development of simulators as analytical platforms
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Long-term urban structural changes and logistics land use
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Logistics policies and solutions related to e-commerce
Recent Publications
Kodera, R., Sakai, T., & Hyodo, T. (2025). Development of a Delivery Time-Period Selection Model for Urban Freight Using GPS Data. Smart Cities, 8(1), 31.
Developing policy instruments related to urban freight, such as congestion pricing, urban consolidation schemes, and off-hours delivery, requires an understanding of the distribution of shipment delivery times. Furthermore, agent-based urban freight simulators use relevant information (shipment delivery time distribution or vehicle tour start time distribution) as input to simulate tour generation. However, studies focusing on shipment delivery time-period selection modeling are very limited. In this study, we propose a method using GPS trajectory data from the Tokyo Metropolitan Area to estimate a shipment delivery time-period selection model based on pseudo-shipment records inferred from GPS data. The results indicate that shipment distance, size, and destination attributes can explain the delivery times of goods. Moreover, we demonstrate the practicality of the model by comparing the simulation result with the observed data for three areas with distinct characteristics, concluding that the model could be applied to urban freight simulation models for accurately reproducing spatial heterogeneity in shipment delivery time periods. This study contributes to promoting smart city development and management by proposing a method to use big data to better understand deliveries and support the development of relevant advanced city logistics solutions.
LinkMotojima, R., Sakai, T., & Hyodo, T. (2024). Development of an online daily goods shopping demand model using internet-based consumption behavior survey data. Transportation Research Record, 03611981241270172.
With the rapid growth of the e-commerce market, how to cater to the demand for last-mile deliveries to households is an important challenge for both policymakers and practitioners. Therefore, the incorporation of e-commerce-driven delivery demand into a freight transportation analysis is required. In this research, we conduct an internet-based survey in Japan to collect data on past in-person and online shopping behaviors and develop a household-based e-commerce demand model that simultaneously estimates e-commerce delivery demand in regard to the total value and order size (or order frequency) using a framework proposed by Sakai et al. Using the estimated model parameters, we conduct a sensitivity analysis using the model to understand the impact of changes in delivery service on e-commerce delivery demand. Focusing on groceries and household goods, we successfully demonstrate the ability of the model framework and obtain insights into the impact of delivery service characteristics on households’ reliance on e-commerce using the model developed based on real-world data.
LinkBook Chapters
Handbook on City Logistics and Urban Freight, Edoardo Marcucci, Valerio Gatta, Michela Le Pira (ed.) Edward Elgar. 2023.
Chapter 5: Evaluating city logistics solutions with agent-based microsimulation
Takanori Sakai, Peiyu Jing, André Romano Alho, Ravi Seshadri, and Moshe Ben-Akiva.
https://doi.org/10.4337/9781800370173.00013
The Routledge Handbook of Urban Logistics, Jason Monios, Lucy Budd, Stephen Ison (ed.) Routledge. 2023.
Chapter 14: Facility Locations in Urban Logistics
Takanori Sakai, Adrien Beziat, and Adeline Heitz.
https://doi.org/10.4324/9781003241478
We have international collaborations with other research groups at the following institutions:
MIT-ITS Lab
University Gustave Eiffel/IFSTTAR (French Institute of Science and Technology for Transport)
Harbin Institutte of Technology, Shenzhen
Rensselaer Polytechnic institute
NYU Tandon School of Engineering
TEAM
Takanori Sakai
Associate Professor, Logistics and Information Engineering
Dr. Takanori Sakai is an Associate Professor at the Department of Logistics and Information Engineering, School of Marine Technology, Tokyo University of Marine Science and Technology (TUMSAT).
Takanori's research interest lies in urban freight transportation and logistics. His current research subject is the advanced urban and transportation simulations for evaluating land use, smart transportation systems, and novel transportation policies. When he was in MIT-ITS lab, he was engaged in the development of SimMobility, an agent-based urban simulation platform for transportation and land-use. He led the development of SimMobility Freight, one of the main modules in SimMobility. Furthermore, he has been conducting studies on how the evolutions in Information and Communication Technology and freight transportation systems transform the logistics land use in metropolitan areas and affect the transportation system and the environment.
Takanori obtained a Ph.D. degree from the Department of Urban Planning and Policy at the University of Illinois at Chicago (UIC) in 2017. Before joining TUMSAT, he was a Senior Postdoctoral Associate at Singapore-MIT Alliance for Research and Technology (SMART), the MIT’s research institute in Singapore. He has an extensive record of research in transport studies and received the Best Paper Awards in the Transportation Research Board (TRB) (US) Urban Freight Transportation Committee in 2017 and 2018 for the research taking novel approaches in urban freight modeling and analysis.
He is currently serving as a committee member of the TRB Freight Transportation and Logistics Committee (AT015) and a director of the Institute for City Logistics.
Aaron Michael Salang
Graduate student (M2)
Yuki Hirabayashi
Graduate student (M2)
Yumi Hazenoki
Graduate student (M2)
Dean Jasper Dizon Tolentino
Graduate student (M1)
Zhe Song (Sonia)
Graduate student (M1)
Azuki Watanabe
Graduate Student (M1)
Graduates
Shinya Tanaka(2025, Master degree)
Research: Development of a simulation model for external freight considering the use of wide-area logistics facilities
Riki Motojima(2025, Master degree)
Research: Development of data-driven heuristics for tour generation in agent-based urban freight simulation
Mei Okura(2025, Bachelor's degree)
Research:Research on Spatial Characteristics of Micro Hubs in Shenzhen and Tokyo
Masahiro Kawasaki(2025, Bachelor's degree)
Research:Research on the use of urban space by large logistics facilities and the impact of e-commerce
Yuri Sakamoto(2025, Bachelor's degree)
Research:Estimation of freight vehicle trip generation model using GPS data
Yuichiro Tanaka(2025, Bachelor's degree)
Research:Research on a framework of urban typology for freight
Mika Taniguchi(2025, Bachelor's degree)
Research:Study on parking time of freight vehicles in cities: Development of a survival model using data from the Tokyo metropolitan area
Yusei Onuma(2024, Bachelor's degree)
Research: Covariance structure analysis of online shopping use: a comparison between Japan and the USA focusing on accessibility to railways
Seita Mori(2024, Bachelor's degree)
Research: Development of a Value Flow estimation method combining two traffic census data sets
Riko Matsushita(2024, Bachelor's degree)
Research: The location potential of factories in the Tokyo metropolitan area
Tatsumi Sato(2024, Bachelor's degree)
Research:Research on the actual state of world cargo ship navigation and port use using AIS data
Kaho Fujiyama(2024, Bachelor's degree)
Research: The impact of transport facility development and the Corona disaster using overnight travel statistics
Virgilio Ramos Jr. (2023, Master degree)
Research: A Framework for Urban Freight Simulation Focusing on Household E-commerce Demand
Shugo Nibe (2023, Master degree)
Research: Freight Vehicle Tour Analysis using Probe Data
Yurika Takano (2023, Bachelor's degree)
Research: "The evolution of urban freight generation: a study of intra- and inter-city truck trips"
Shota Iizuka (2022, Barchelor's degree)
Research: "Decision factors for online and offline shopping: analysis using the NYC Mobility Survey data under the coronavirus pandemic"
Kohei Santo (2022, Barchelor's degree)
Research: "Study of logistics facility locations for e-commerce"
Visiting scholars in the past
Lin Xiaohong
Nov 2023 - Feb 2024, Master student at Harbin Institute of Technology, Shenzhen
Huang Yinghuan
Nov 2023 - Feb 2024, Master student at Harbin Institute of Technology, Shenzhen
Coriolan Gout
Oct-Dec,2022 from the University of Paris 1 Panthéon-Sorbonne
PROJECT
Development of Value Flow Calibration Method Combining Two Transportation Census Data
FY2024 Grant-in-Aid for Scientific Research (Grant-in-Aid for Scientific Research Fund), Grant-in-Aid for Scientific Research (C): Co-Investigator/24K07697
2024/4～2027/3
4,160 thousand yen
Implementation of an agent-based urban freight model and simulation analysis
FY2023 Grant-in-Aid for Scientific Research (Grant-in-Aid for Scientific Research Fund), Grant-in-Aid for Young Scientists: Principal Investigator/23K13421
2023/4～2025/3
6,240 thousand yen
Development of a supply-side model for e-commerce transportation analysis
FY2021 Grant-in-Aid for Scientific Research (Grant-in-Aid for Scientific Research Fund), Research Activity Start-up Support: Principal Investigator/21K20445
2021/9～2022/3
2,730 thousand yen
Research on traffic trend analysis method using existing data
Joint research with Expressway Technical Research Institute, Inc.
2020/10～2022/2
1,760 thousand yen (shared)
Technical Research and Development of Road Infrastructure Considering Double-Connected Trucks and Freight Vehicles in Formation
Commissioned research for "Research and development of technology that contributes to improving the quality of road policy" by the Road Bureau, Ministry of Land, Infrastructure, Transport and Tourism
2021/5～2022/2
24,880 thousand yen (shared)