TNK118 · 6 credits · Advanced level (A1N) · Transportsystem
Transport Demand Forecasting
Active · next start VT 2027
62%
passed the latest ordinary exam
TEN1 · 20 Mar 2026 · 13 students
68%
passed the ordinary exams, all sittings over the last 5 years
TEN1 · 53 students
Part of 2 programmes
Exam
TEN1 Written Examination
- 5
- 4
- 3
- U
Ordinary exams
68% passed · 53 students
- 62%13
- 69%16
- 67%12
- 75%12
Re-exams
64% passed · 11 students
- 67%6
- 60%5
- Pass the re-exam: 64% (11 students), compared with 68% (53 students) on the ordinary exam
- Get 4 or 5: 34% (64 students)
Show small sittings (7)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 0%1
- 75%4
- 0%1
- 50%2
- 100%1
- 67%3
- 67%3
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Hand-in or lab
LAB1 Laboratory Work
- G
Main rounds
100% passed · 38 students
- 100%10
- 100%10
- 100%6
- 100%12
Later rounds
100% passed · 6 students
- 100%6
- Pass a later round: 100% (6 students), compared with 100% (38 students) on the ordinary exam
Show small sittings (4)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%3
- 100%4
- 100%1
- 100%4
About the course
Aim
The course aims to provide basic knowledge in planning and forecast based on modelling of passenger transports in the traffic systems. The mathematical models analyzed in the course aims at estimating the travel demand and the effect of this demand on the transport system. The course provides an overview of problems, settings and applications in the area of traffic planning, and gives insights into how traffic models may be used for the analysis of traffic systems to make the system more efficient, safer and more environmentally friendly now and in the future. Furthermore, the course will help the student to gain insights into the underlying theories on which the models are based. The course covers both supply and demand modelling, and the focus is on-demand modelling.
After the course, the student shall be able to:
- Describe the basics for traffic planning and traffic modelling such as trip generation and trip distribution
- Motivate and derive basic discrete choice models
- Apply choice models for modelling demand, mode and route in a traffic network
- Formulate and use trip generation and distribution, route choice, and demand models for evaluating future traffic scenarios
- Estimate parameters in discrete choice models
- Describe and analyze route choice models and assignment methods for network assignment
- Update demand matrices from flow and speed observations
- Make use of tools for applying the models for sustainable development of future transport systems.
Content
- Introduction to traffic planning and traffic simulation
- Classification of traffic models
- Discrete choice models
- Parameter estimation for choice models
- Route choice model and assignment principles for network assignment
- Experiments with network assignment models
- OD-estimation
- Application of the traffic forecasting models on capacity and pricing problems
- Examiner
- Clas Rydergren
- Scheduled hours
- 44 h
- Main field of study
- Transportsystem