| Academic Year |
2026Year |
School/Graduate School |
Graduate School of Advanced Science and Engineering (Master's Course) Division of Advanced Science and Engineering Transdisciplinary Science and Engineering Program |
| Lecture Code |
WSQN0501 |
Subject Classification |
Specialized Education |
| Subject Name |
Transportation Engineering |
Subject Name
（Katakana） |
|
Subject Name in
English |
Transportation Engineering |
| Instructor |
CHIKARAISHI MAKOTO |
Instructor
(Katakana) |
チカライシ マコト |
| Campus |
Higashi-Hiroshima |
Semester/Term |
1st-Year, First Semester, 1Term |
| Days, Periods, and Classrooms |
(1T) Mon9-10,Weds9-10：IDEC 201 |
| Lesson Style |
Lecture |
Lesson Style
(More Details) |
Face-to-face |
| The course is primarily conducted in person; however, some sessions may be held online when necessary. |
| Credits |
2.0 |
Class Hours/Week |
4 |
Language of Instruction |
E
:
English |
| Course Level |
6
:
Graduate Advanced
|
| Course Area（Area） |
25
:
Science and Technology |
| Course Area（Discipline） |
13
:
Civil Engineering |
| Eligible Students |
1st year master student |
| Keywords |
transportation, travel behavior analysis, traffic flow analysis, transport network analysis |
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Class Objectives
/Class Outline |
This course provides foundational methods in transportation engineering, with emphasis on data-informed problem solving for planning and operations. Topics include transportation data handling, travel demand analysis, network modeling, traffic flow analysis, and practical interpretation of model outputs for engineering and policy decisions. |
| Class Schedule |
Course Orientation and Scope of Transportation Engineering
Transportation Data Foundations and Data Quality
Emerging Data Sources and Methods in Transportation
Introduction to Travel Demand Analysis
Travel Behavior Analysis
Choice Estimation and Behavioral Interpretation
Sensitivity, Validation, and Policy Implications
Network Representation and Link Cost Functions
User Equilibrium and System Optimum
Assignment Algorithms and Practical Issues
Traffic Flow Measurement and Fundamental Diagram
Traffic Flow Models and Applications
From Models to Practical Applications
Report Workshop and Q&A
Final Report Presentations and Course Wrap-up |
Text/Reference
Books,etc. |
Sheffi, Y. (1985). Urban Transportation Networks: Equilibrium Analysis with Mathematical Programming Methods. Prentice-Hall.
Ortúzar, J. de D., & Willumsen, L. G. (2011). Modelling Transport (4th ed.). John Wiley & Sons.
Koppelman, F. S., & Bhat, C. R. (2006). A Self-Instructing Course in Mode Choice Modeling: Multinomial and Nested Logit Models.
Train, K. E. (2009). Discrete Choice Methods with Simulation (2nd ed.). Cambridge University Press.
Treiber, M., & Kesting, A. (2025). Traffic Flow Dynamics. Springer Nature Switzerland. |
PC or AV used in
Class,etc. |
Handouts, Microsoft Teams, moodle |
| (More Details) |
Powerpoint |
| Learning techniques to be incorporated |
|
Suggestions on
Preparation and
Review |
Before each class, review key concepts; after class, summarize the methods and try to implement them. |
| Requirements |
It is recommended to have some basic knowledge on “probability and statistics” and “optimization”. |
| Grading Method |
1. Mini-Quizzes: 50%
2. Final Individual Report: 50% |
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| Message |
|
| Other |
|
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. |