Transportation and Urban Design Studio E 2021

for Graduate School of Civil Engineering in 2021 Autumn Semester 1 (A1)

Lecturers

• Prof. Eiji Hato (Professor, Transport Research and Infrastructure Planning (TRIP) Lab.)
• Prof. Takamasa Iryo (Professor, Transport Research and Infrastructure Planning (TRIP) Lab.)
• Assoc. Prof. Ryuichi Shibasaki (Associate Professor, Department of Systems Innovation, School of Engineering)
• Assist. Prof. Junji Urata (Assistant Professor, Transport Research and Infrastructure Planning (TRIP) Lab.)

Place and Time

Online, on Monday and Thursdays 13:00-14:45. Please check the online URL from ITC-LMS

Purpose and Contents of the Course

This course focuses on learning some of methodologies to analyze transportations and regions, which are sometimes vulnerable to natural hazards. In addition to it, getting used to the essence of the basic way of theoretical and mathematical thinking in planning is another main target. For fulfilling these purposes, we choose four topics: 1) Traffic flow modelling, 2) Logistics management and analysis, 3) Statistics and Machine Learning, 4) Travel behavior modelling.
Syllabus

Schedule of the Course

• Oct. 4 Introduction

Topic 1: Transportation Modelling and Statistics, by Prof. Urata and Prof. Hato

You will use your laptop which are installed R in Topic 1. Please download R from the R's official website.

• Oct. 07 Travel Behavior Modelling (1)
• Oct. 11 Travel Behavior Modelling (2)
• Oct. 28 Presentation (Travel Behavior Modelling (3))

Topic 2: Traffic Flow Theory and Modelling, by Prof. Iryo and Prof. Hato

• Oct. 14 Traffic Flow Theory and Modelling (1)
• Oct. 21 Traffic Flow Theory and Modelling (2)
• Oct. 25 Traffic Flow Theory and Modelling (3) and Final Exercise

Topic 3: Statistics and Machine Learning, by Dr. Shafique and Prof. Hato

• Oct. 26 Statistics and Machine Learning (1): Introduction to Machine Learning
• Oct. 28 Statistics and Machine Learning (2): Machine Learning vs. Discrete Choice Modelling
• Nov. 02 Statistics and Machine Learning (3): Travel Mode Detection using Machine Learning, and Final Exercise

Topic 4: Logistics Management and Analysis, by Prof. Shibasaki and Prof. Hato

• Nov. 08 Global Logistics Modelling & Analysis (1)
• Nov. 11 Global Logistics Modelling & Analysis (2)
• Nov. 15 Global Logistics Modelling & Analysis (3)

Schedule of the Course

Assignments in each of the three topics (22 points @ 4), and attendance points for classes (12 points)
Your attendance is confirmed using the history function of zoom.
Please let Prof. Urata know if you cannot attend ontime because of covid-19-entry-problem. We share the lecture video, and set other way for attendance point.

Lecture materials and Bibliography

• Train, K., Discrete Choice Methods with Simulation Second edition, Cambridge University Press, 2009.
• Sheffi, Y., Urban transportation network, Pretince Hall, 1985.
• Venables, W. N., Smith, D. M., and the R Core Team, An Introduction to R, 2017.
• Paradis, E., R for Beginners, 2005.

Questions?

• If you have a question, please ask Prof. Urata (urata{at}bin.t.u-tokyo.ac.jp).
• We can provide video which is recorded the talk when your attendance is interrupt by internet-connection problem. Please contact to Prof. Urata as soon as possible.