21st Summer Course (Behavior Modeling in Transportation Networks)

The Summer Course was held on September 23rd to 25th, 2022 for both online and on-site participants at the University of Tokyo Hongo Campus. Students and researchers from different universities and organizations gathered to join the event. The 3-day course provided a vast knowledge of different behavior modeling techniques for transportation networks and insights from keynote speakers, professors, and researchers.

Laboratory Introduction

Short Tour to Homeikan for International Students

3-Day Program


8:30 – 8:40   Opening Ceremony

8:40 – 10:00 Deterministic/Stochastic Demand Optimization for Urban Logistics Prof. Teodor Gabriel Crainic (Université de Montréal)

10:00 – 11:00 Coding Tutorial for Beginners

11:00 – 12:00 Feedback for Group Work (E & J)

12:00-13:30 Lunch

13:30-14:00 Professor Jana
14:00-14:30 Professor Parady
14:30-14:45 Break
14:45-15:15 Professor Chikaraishi
15:15-15:45 Professor Shafique
15:45-16:15 Professor Yaginuma
16:15-16:30 Break
16:30-17:00 Professor Oyama

17:10 – 18:30 Laboratory Introduction


9:00 – 10:30 Keynote Lecture (lecture in Japanese)
10:30 – 11:00 Break

11:00 – 12:00 Keynote Lecture (lecture in Japanese)

12:00-13:00 Lunch

13:00-14:30 #1 BinN Research Seminar: Latest Optimization Theory and Network Problems

  1. Meta-reinforcement learning for multi-modal multi-region coordinated control,
     Takao Dantsuji (Kanazawa University)
  2. A structured programming method for matching heterogeneous demand in mixed freight and
     passenger network, Fuga Mayuzumi (UTokyo)
  3. Optimization of inventory transportation strategy, considering the procurement of goods by
     the affected population, Riki Kawase (Tokyo Institute of Technology)

14:30-15:00 Break + Transfer

15:00-18:00 Group work and feedback @Homeikan (edited) 


10:30-12:00 BinN Research Seminar 2: Can Urbanists Change Cities with Diverse Mathematics? (E)

  1. Modeling and Case Study of Land Transaction Mechanism with Gale-Shapley
    Algorithm, Risa Kobayashi (UTokyo)
  2. Characteristic of transport network based on the eigenvalue analysis, Hiroe
    Ando (Kumamoto University)
  3. Bayesian sample selection model for dealing with non-randomly missing travel
    behavior outcomes, Hajime Watanabe (UTokyo)

12:00 – 13:00 Lunch Break
13:00 – 14:00 Keynote Lecture
14:00-15:30 Watching Presentation Videos of Groupwork
15:30-16:30 Discussion about Presentation
16:30-16:50 Comments from young researchers
16:50-17:00 Break
17:00 – 18:10 BinN Young Prize Ceremony (E & J)

Invited talks by Prof. Iwan and Prof. Wido from Diponegoro University

We had invited talks by the guests from Diponegoro University, Iwan sensei, and Wido sensei. It was a nice opportunity to understand the state-of-the-art researches in Indonesia in the field of urban and regional planning.

We also have an informal “second” final master defense for the linkage students. Well done!

Place: IDEC large conference room

Date & time: 15:00-17:45 on September 21, 2022


(1) Invited talks

15:00-15:45  Prof. Wido Prananing Tyas

“Strategy and Innovation of Micro and Small Enterprises for Local Development toward 4.0 Era”

15:45-16:30  Prof. Iwan Rudiarto

“Building Scenario for Future Spatial Formations and Development”

16:30-16:45 Break

(2) Presentations of students under Linkage program

16:45-17:05 Dopit Saputra

17:05-17:25 Kiki Nidya Stephanie

17:25-17:45 Melanton Hendra Siregar

Iwan sensei
Iwan sensei
Wido sensei
Wido sensei


Four master students have just completed their study in our lab. Many congratulations on your graduation, Ei Ei, Alex, Hulio, and Hendra san!

PS. We are lucky enough to have two guests, Iwan sensei and Wido sensei, from Diponegoro University on such a memorial day.

Seminar on Recursive Logit Model

A recursive logit model and its extensions can be utilised for a wide range of issues in the urban and transportation field, such as modelling activity-travel behavior in a time-space prism, and modelling route choice behavior on a large-scale road network. In this study camp, we first review existing studies in details and the prepare programming codes to execute recursive logit model and its extended versions.

September 9

9:00 Gathering at IDEC

9:00-12:00 Travelling to Matsuyama

12:00-13:00 Lunch

13:00-15:00 Fosgerau et al. (2013)  by Zafirah binti Abdul Gani

15:00-15:30 Break

15:30-18:30 Mai et al. (2015) by Nur Diana Safitri

18:30-20:30 Oyama and Hato (2017) by Natsuki Nagasaka

20:30 Enjoy the night

September 10

8:30-10:00 Vasberg et al. (2019) by Makoto Chikaraishi

10:00-12:00 Oyama et al. (2022) by Keishi Fujiwara

12:00-13:00 Lunch

13:00-15:00 Structural estimation methods by Hiroki Noguchi

15:00-18:00 Enjoy Matsuyama

18:00-21:00 Back to Saijo

Seminar on Machine Learning

For about a quarter of a century, machine learning methods have been widely applied to traffic problems, including rule-based and activity-based model building.
For about a quarter of a century, research has been widely conducted on the application of machine learning methods to traffic problems, including the construction of rule-based activity-based models. In recent years, there have been a number of studies that extend machine learning methods in a way that is consistent with traffic theory.
Recently, there have been a number of studies that extend machine learning methods in a way that is consistent with traffic theory. Such machine learning methods that are consistent with traffic theory
with traffic theory are superior not only in terms of theoretical validity, but also in terms of improving prediction accuracy.There have been several reports on machine learning methods that are consistent with traffic theory. In this workshop, we will discuss the academic and technical aspects of the transportation field, where the use of big data and passive data is becoming more and more widespread.

The study group will review the application and extension of machine learning methods in the field of transportation, taking into account the academic and practical situation in the field of transportation, where the use of big data and passive data is becoming more and more widespread.
The aim of this workshop is to organise the application and extension of machine learning methods in the field of transportation, where the use of big data and passive data is becoming more and more widespread.

8/29: Lecture

13:20-13:30 Explanation of the purpose of the study group meeting

13:30-14:30 Makoto Chikaraishi (Hiroshima University): Discrete Choice Models and Neural Networks

14:30-15:00 Break

15:00-16:00 Yu Fujiwara and Goki Sato (Hiroshima University): Discrete Choice Models and Association Networks

16:00-17:00 Yoshinao Ishii (Toyota Central R&D Labs.): Entropy models and Tucker decomposition

9:00-10:00 Keishi Fujiwara and Zafirah Binti Abdul Gani (Hiroshima University): Inverse reinforcement learning and recursive logit

10:00-11:00 Tetsuro Sakai and Motoki Takai (Hiroshima University): Road Network Reliability Evaluation and Surrogacy Model

11:00-11:30 Lecture: Takashi Maeoka (Kyushu Regional Police Bureau, National Police Agency): Infrastructure Longevity in Islands Area and Application of Big Data in Police

Congratulations Ei Ei and Hendra!

Two lab members just finished their master thesis on August,8th.

Melanton Hendra Siregar
“The Impact of Railway Stations Development on Land Price: A Case in West Japan”


Ei Ei Tun
“Emergency Shelter Location – Allocation with Time – Varying Demand: A Case in Higashi – Hiroshima”


They did incredible work hitting this award! I’m very happy that both of them got the Excellent Master Thesis Awards (Hendra san got the First Place of Excellence, and Ei Ei san got the Second Place of Excellence). Congratulations and best wishes for your continued success in the future. I wish nothing but the best for you.


[Excellent master thesis awards] The 1st semester in 2022